us-stocks-analysis

US stocks analysis by an adversarial investment committee. Legendary-investor personas independently research a thesis, attack each other's cases against a shared evidence ledger (sentiment, smart money, SEC fundamentals), and reconcile into a verdict with recorded dissents. Structured rubrics keep every number sourced, on any model. Includes five quick data workflows. Use for stock research, investment thesis, bull case vs bear case, due diligence on a ticker, should I buy this stock, deep dive on a company. Read-only. No trading, no purchases, no write operations, no wallet access.

Senti@thesentitrader

Install

openclaw skills install @thesentitrader/us-stocks-analysis

US Stocks Analysis: The Investment Committee - SentiSense

Adversarial investment-committee analysis for US equities. For quick data asks, five expert workflows synthesize price, sentiment, smart money, analyst ratings, and AI insights into terminal-grade briefs. For thesis-grade questions ("should I own NVDA for 3 years?"), the skill convenes a committee of legendary-investor personas that independently research, then attack each other's cases against a shared evidence ledger, then reconcile into a verdict with recorded dissents. The structure is designed so that even a small local model, following the templates literally, produces grounded, multi-perspective analysis instead of consensus mush. Read-only API. No trading, no purchases, no write operations, no wallet access.

Base URL: https://app.sentisense.ai Website: https://sentisense.ai Full API reference: https://sentisense.ai/skill.md Authentication: API key via X-SentiSense-API-Key header. Get a free key at https://app.sentisense.ai/get-api-key

What This Skill Is

Two layers, one routing decision per user ask:

Quick Reads. Five proven data workflows (brief, smart money, divergence, pre-earnings, sector rotation) for questions that want a dense factual answer in five lines.
The Investment Committee. A structured adversarial debate between investor personas for questions that want judgment: is this thesis sound, what would break it, where do serious people disagree.

The committee is not roleplay flavor. It is an error-correction machine. A single free-form pass produces a plausible, agreeable, number-fuzzy blob. Forcing the same model to (a) build independent persona cases, (b) attack them against evidence, and (c) reconcile the survivors is how you extract rigorous judgment from any model, including small local ones. The adversarial structure IS the intelligence.

The governing line for everything below: the intelligence lives in the skill's structure, not the model. A weak model that fills these templates in order produces analysis it could not have produced free-form. If you are a strong model, the templates are still binding: they are what keeps you honest.

One invariant everything serves: the committee must surface real disagreement grounded in real evidence, and must never collapse into consensus mush or theater.

Use & Disclaimer

This skill is an educational data interface to SentiSense's read-only Data APIs plus public primary sources (SEC EDGAR, FRED). Output is informational only. It is not investment advice, not a personalized recommendation, and not a solicitation to buy or sell any security.

The user is responsible for their own decisions. SentiSense (SentiSense Labs LLC) and the skill author disclaim liability for any actions taken or not taken based on output produced through this skill.

Persona seats are teaching archetypes built from publicly documented investing philosophies. They are not affiliated with, endorsed by, or statements from the named individuals. A persona is a lens, not a jailbreak: precedence is always platform safety, then this skill's grounding and no-advice rules, then persona instructions. A custom persona can change the analytical lens; it can never override grounding, disclaimers, or the no-advice rule.

Use of the SentiSense API is subject to the API Terms of Service and Terms of Service.

Authentication and how to fetch

Set the key once in the environment, and say who is calling:

bash

export SENTISENSE_API_KEY=...               # free key: https://app.sentisense.ai/get-api-key
export SENTISENSE_SKILL=us-stocks-analysis  # this skill
export SENTISENSE_AGENT_NAME=my-agent       # optional: what your agent calls itself

Fetch with the CLI. Every workflow below leads with the official SentiSense CLI, which ships inside the sentisense npm package, so there is nothing to install and npx runs it on demand. Use version 0.44.0 or newer. It stamps both identity variables for you.

bash

npx -y sentisense@0.47.1 health              # reachability, key validity, latency, one call
npx -y sentisense@0.47.1 quote NVDA --json

--json returns the exact API response, envelope and all, nothing renamed, so every field path in this file reads the same whichever way you fetched. Exit codes: 0 ok, 2 usage, 3 auth, 4 not found, 5 rate limited, 6 network. help <command> prints a command's flags.

Fetch without the CLI. Nothing here requires it. Each step carries the endpoint behind it, and the Fetch Reference at the bottom lists them all. Parameter and schema detail lives in the sentisense skill and at https://sentisense.ai/skill.md; it is not repeated here.

bash

curl -H "X-SentiSense-API-Key: $SENTISENSE_API_KEY" \
  -H "User-Agent: ClaudeCode/2.1 (us-stocks-analysis)" \
  "https://app.sentisense.ai/api/v1/stocks/price?ticker=AAPL"

Over raw HTTP the User-Agent carries the identity the CLI would have stamped: name your agent runtime and this skill, for example OpenClaw/1.4 (us-stocks-analysis). Substitute your own runtime and version if neither matches. Optional, and it is what tells us this skill has real integrations behind it, so it gets prioritized and you get notice before it changes.

All SentiSense endpoints require an API key. Free tier (1,000 req/month, 30 req/min) covers everyday use, including full committee runs. PRO ($15/mo) removes the monthly cap (unlimited, 300/min) and unlocks full preview-gated history.

Tier	Quota	Rate
Free	1,000 req/month	30 req/min
PRO	Unlimited	300 req/min

Anonymous calls return 401 api_key_required. EDGAR and FRED (used for fundamentals and macro) are public and need no key; see Fetch safety before calling them.

Resolve a company name before the first data call. Every quick read and every committee step below takes a canonical ticker. When the user names the company instead ("brief me on tesla", "should I own alphabet for 3 years"), resolve it first, over REST (there is no CLI command for this yet): GET /api/v1/kb/entities/search?q={name}&type=company&limit=5 returns a bare array of {name, urlSlug, type, ticker}, best match first. Take the first match with a non-null ticker; a tracked subsidiary can outrank its listed parent ("google" returns Google LLC with ticker: null before Alphabet GOOGL). Several plausible ticker-bearing matches is a one-line clarification, an empty array is a stated miss, and neither starts a fan-out. Never uppercase the name into a symbol and never take the ticker from memory: memory is fine for TSLA and wrong for renamed issuers, ADRs and share classes, and a wrong symbol fails loudly over the CLI (exit 4, "unknown ticker") but quietly over REST, where insider/trades/{T} returns an empty data: [] that reads like a quiet name. An exact ticker the user typed skips this step.

Routing Gate: Quick Read or Committee?

Decide once, at the top of every turn:

The user asks...	Route
A factual data question ("NVDA price?", "brief me on AAPL", "what's the smart money doing?", "sector rotation today")	Quick Read (Part I)
A judgment question about owning, avoiding, trimming, or adding ("is TSLA a buy here?", "should I hold NVDA for 5 years?", "red-team my COIN thesis", "what would Buffett think of PLTR?")	The Committee (Part II)
A judgment question but the user wants it fast or the context window is small	Committee, lite path (see Degradation ladder)

Do not convene five personas to answer a price quote. Do not answer a thesis question with a data dump and no judgment. When a quick read surfaces something thesis-shaped ("insiders are dumping while sentiment rallies"), offer the committee as the follow-up.

Part I: Quick Reads

Each is a natural-language intent, an ordered set of calls, and a synthesis shape. Fetch steps lead with the CLI; the REST: in parentheses is the same call over plain HTTP, and a step with no CLI line is REST only. Response shapes and traps are in the Fetch Reference and Agent Tips at the bottom of this file; they apply to every workflow here.

Quick Read 1: "Brief me on $TICKER"

npx -y sentisense@0.47.1 quote {T} --json for price + day change (currentPrice, changePercent). REST: GET /api/v1/stocks/price?ticker={T}
GET /api/v2/metrics/entity/{T}/metric/sentiment for the 7-day sentiment trend (no CLI command: the CLI's sentiment returns the Score, not this polarity series)
npx -y sentisense@0.47.1 insiders {T} --days 90 --json for insider activity (.data[]). REST: GET /api/v1/insider/trades/{T}?lookbackDays=90
npx -y sentisense@0.47.1 analysts {T} --json for the target band (.consensus.data). REST: GET /api/v1/analyst/{T}/consensus
npx -y sentisense@0.47.1 insights {T} --json for AI insights (.data[]; take the first item for the headline, check its generatedAt and flag age). REST: GET /api/v1/insights/stock/{T}

Synthesize as: "AAPL $190.20 (+1.2%). Sentiment +0.34 and rising (+0.06 over 7d). 3 insider buys in 90d, no sells. Analyst band $180-$250 (mean $210, 33 analysts, Buy). Latest insight: 'Margin guide raised, services beating consensus.'" Five signals, one tight brief, done.

Quick Read 2: "What's the smart money doing this week?"

GET /api/v1/insider/cluster-buys?lookbackDays=7 (no CLI command)
npx -y sentisense@0.47.1 congress --days 7 --limit 50 --json (.data[], filter to PURCHASE). REST: GET /api/v1/politicians/activity?lookbackDays=7
GET /api/v1/analyst/activity?lookbackDays=7&actionTypes=UPGRADE (no CLI command; server-side filter, CSV of UPGRADE/DOWNGRADE/INITIATE/REITERATE/OTHER)

Intersect the three ticker lists; report names in 2+ buckets with a one-liner each ("NVDA: 4 insiders bought ($2.1M), 1 senator purchased $50k-$100k, 2 upgrades"). Convergence is the signal. Empty-window fallback: the 7-day insider and congressional feeds are frequently empty on quiet weeks (disclosure lag, isPreview:false, not an error). Widen the empty bucket to 30 days (--days 30, or lookbackDays=30 over REST), say so in the header, and if the intersection is still empty report the strongest single-bucket names as runners-up rather than forcing convergence or returning a blank. Cite the trade date (transactionDate), not the 7-day disclosure window: STOCK Act filings lag weeks to months, so a name surfacing this week may reflect a much older trade (see the Committee disclosure rule).

Quick Read 3: "Find divergence stocks"

REST only, all three steps: the CLI exposes no popular list, no price chart, and no per-metric time series.

GET /api/v1/stocks/popular for candidates
Per ticker: GET /api/v1/stocks/chart?ticker={T}&timeframe=1M (intraday bars, not daily closes; for a 7-day change filter to bars with timestamp >= now-7d, compare first vs last)
Per ticker: GET /api/v2/metrics/entity/{T}/metric/sentiment (default 7-day window). If the series has fewer than 2 points, treat the trend as insufficient data and EXCLUDE the ticker rather than computing a bogus delta. With 2+ points, sentimentChange = last minus first (each read via metricValue.value.value, a polarity in [-1,1]). Thin-sample guard: a window-edge point built on a handful of mentions can dominate the delta (a lone 1-mention day at +/-1.0 swamps everything). Only the Score (sentisense_score) series carries metricValue.properties ({bull, bear, directional}; sentiment points have empty properties), so read the sample size from the Score point for the same window via properties.directional, the day's directional (bull + bear) mention count (or fetch /metric/mentions); if the first or last point is thin (roughly under 5 directional mentions), use the nearest robust point or average the first and last two instead of trusting a single noisy edge. Note directional counts non-neutral mentions only, so it is always at or below the /metric/mentions total. Do not reach for metricValue.stats.count: it is the daily-bucket count and is always 1.
Same scale before ranking. priceChangePct is a percentage; sentimentChange is a raw polarity delta in ~[-2,2]. Scale: sentimentChangeScaled = sentimentChange * 100. Apply this exact scaling so any two implementations agree. Bucket by sign before ranking: a divergence requires price and sentiment to move in OPPOSITE directions, so bullish divergence is priceChangePct < 0 and sentimentChangeScaled > 0, and bearish divergence is priceChangePct > 0 and sentimentChangeScaled < 0. Same-sign pairs (both moved up, or both moved down) are not divergences no matter how large the gap between them, exclude them. Within each bucket, rank by |priceChangePct - sentimentChangeScaled| and report the top 5.

Synthesize as: "Bullish divergence (price down, sentiment up): TSLA -8% / sentiment +12%. Bearish divergence: COIN +14% / sentiment -9%."

Quick Read 4: "Pre-earnings sentiment check on $TICKER"

GET /api/v1/calendar/earnings?ticker={T} for the next report date (data.earnings[0].earningsDate + confirmed); empty means outside the forward window: fall back to periodLabel from step 5 for timing framing. No CLI command: the CLI's earnings calendar mode takes --week, --from, --to, never a ticker
GET /api/v1/stocks/{T}/profile for sector context (no CLI command)
GET /api/v2/metrics/entity/{T}/metric/sentiment?startTime={now-30d epoch ms}&endTime={now epoch ms} for the 30-day trend (no CLI command)
npx -y sentisense@0.47.1 insiders {T} --days 60 --json (.data[]). REST: GET /api/v1/insider/trades/{T}?lookbackDays=60. Filter before tallying: only transactionCode P and S are directional, and codes A, G, M and F (awards, gifts, exercises, tax withholding) are not, so an all-award window is zero insider activity, not a wave of it
GET /api/v1/analyst/{T}/estimates for the EPS band (data.estimates[0], plus data.surprises[] history; no revenue figure, no revision history). No CLI command
npx -y sentisense@0.47.1 analysts {T} --days 30 --json for rating changes (.actions.data[]; the same call also carries .consensus.data, so it covers the analyst band for free). REST: GET /api/v1/analyst/{T}/actions?lookbackDays=30

Synthesize as: "AAPL ER in 5d. Sentiment +0.22 over 30d, trending up. Insiders: 2 sells, 0 buys (neutral-to-bearish). EPS consensus $1.52 (range $1.48-$1.55, 28 analysts); beat 3 of last 4. 3 upgrades in 30d. Setup: mixed-bullish."

Quick Read 5: "Sector rotation today"

npx -y sentisense@0.47.1 mood --json, REST: GET /api/v2/market-mood. Either way the composite is nested under market (market.currentScore, market.phase, market.weeklyChange), NOT at the root. sectors is a string-keyed dict; labels have historically overlapped (Technology vs Information Technology, Healthcare vs Health Care), so if both members of a pair appear, dedupe by keeping the higher-scoring variant before ranking. A clean 11-key response is the common case.
For sectors with weeklyChange > +5 or < -5: GET /api/v1/insights/market (no CLI command; the CLI's insights is per-ticker), client-side filter data[] to insights mentioning tickers in that sector (use /stocks/{T}/profile sector, which is reliable; descriptions often omits sector, skip rather than guess).
Report top 2 and bottom 2 movers with one driver insight each.

Synthesize as: "Market mood 62 (Greed, +4 wk). Greed: Technology 71 (+3.2), Comms 68. Fear: Energy 31 (-6), Utilities 36. Top driver: NVDA 'Data-center revenue accelerating.'"

Part II: The Investment Committee

The pipeline (the rail you cannot skip)

Do exactly one step, finish it, then move on. Do not start the debate before the Evidence Ledger is filled. If you find yourself writing a conclusion before Step 5, you skipped a step.

text

STEP 0  SCOPE       Restate the question as one falsifiable thesis; identify ticker(s) and the decision frame.
STEP 1  GATHER      Fill the Evidence Ledger. Every number from a source. Unsourceable = [NOT AVAILABLE]. Do NOT analyze yet.
STEP 2  BASE CASE   Fill the neutral Base Thesis template using ONLY ledger rows.
STEP 3  CONVENE     Pick the panel (default 5, or the user's named investors). Load each persona's worksheet.
STEP 4  DEBATE      Run rounds R1-R3 (sealed theses, cross-examination, rebuttals).
STEP 5  SYNTHESIZE  The Chair runs R4 and fills the Committee Verdict template.
STEP 6  GATE        Run the Pre-Flight Checklist. Fail closed on fabrication.

Each step below is its own section with its template inlined, so reading top to bottom IS executing the procedure.

STEP 0: Scope

Write one line before anything else:

text

THESIS UNDER REVIEW: <ticker(s)>: "<one falsifiable sentence>"   DECISION FRAME: <own / avoid / trim / add>, horizon <N years>

Examples: NVDA: "At today's price, NVDA is attractive for a 3-5 year holder." or COIN: "COIN's earnings quality is too weak to support its multiple." If the user gave a vague ask ("thoughts on TSLA?"), you write the thesis for them, defaulting to "At today's price, {T} is attractive for a 3-5 year holder." The committee votes on this sentence and nothing else. A vague thesis produces a vague debate; make it falsifiable.

STEP 1: The Evidence Ledger

The single most important artifact. Every downstream claim must cite a ledger row ID ([E3]). A fact not in the ledger does not exist. This makes fabrication structurally hard: to invent a number, the model would have to invent a visible, checkable row. Fill the ledger completely BEFORE any analysis. Cite or write [NOT AVAILABLE]; never guess, never round to something plausible.

The three source tiers and the routing law

Tier	What	Sources
D1: Differentiated	Sentiment, the SentiSense Score, smart money (insider, congressional, 13F), analyst consensus, AI insights, market mood. The edge layer: things not in a 10-K.	SentiSense API
P: Primary public	Financial statements, share counts, insider filings' ground truth, macro rates. SentiSense does NOT serve financial statements; fundamentals live here.	SEC EDGAR (10-K, 10-Q, 8-K, Form 4, DEF 14A, XBRL), FRED, company investor relations
S: Secondary	Reputable press, model reasoning. Corroborates; never the sole basis for a number.	Web search, if the host has it

Routing law: for any claim, use the lowest tier that owns that fact. A financial-statement number comes from Tier P, never from memory. Sentiment and positioning come from D1. Macro from FRED. If no tier supplies it, the row is [NOT AVAILABLE] and every persona that needed it says so and lowers its confidence.

Filling the D1 rows

One block fills every SentiSense row. --json is the exact API response, so the field paths below are the ones the ledger rules refer to.

bash

npx -y sentisense@0.47.1 quote {T} --json              # E1  price, day change
npx -y sentisense@0.47.1 sentiment {T} --json          # E11 .sentiment.data.sentisenseScore
npx -y sentisense@0.47.1 insiders {T} --days 90 --json # E12 .data[]
npx -y sentisense@0.47.1 congress {T} --days 90 --json # E13 .data[]
npx -y sentisense@0.47.1 flows {T} --json              # E14 .data.holders[], quarter resolved
npx -y sentisense@0.47.1 analysts {T} --json           # E15 .consensus.data
npx -y sentisense@0.47.1 mood --json                   # E17 .market
npx -y sentisense@0.47.1 options {T} --json            # E19 .data, optional

sentisenseScore is null until the day's batch lands, so fall back to .sentiment.data.sentisenseScoreAvg30d and label the row with its asOf.

Without the CLI: each command's endpoint is in the Fetch Reference at the bottom, one line each. Two rows are REST either way, having no CLI command: GET /api/v2/metrics/entity/{T}/metric/sentiment fills E10 (sentiment polarity and its 7-day trend) and GET /api/v1/calendar/earnings?ticker={T} fills E16 (next earnings date).

The ledger template

text

### EVIDENCE LEDGER: {TICKER}   (filled {date})
| ID  | Fact                            | Value | As-of / Period      | Class     | Tier | Source |
|-----|---------------------------------|-------|---------------------|-----------|------|--------|
| E1  | Price + day change              | $__ / __% | 15-min delayed  | realtime  | D1   | SS /stocks/price |
| E2  | Revenue (TTM or latest FY)      | $__   | __ (state FY end)   | quarterly | P    | EDGAR XBRL |
| E3  | Net income (TTM or latest FY)   | $__   | __                  | quarterly | P    | EDGAR XBRL |
| E4  | Operating cash flow             | $__   | __                  | quarterly | P    | EDGAR XBRL |
| E5  | Free cash flow (E4 minus capex) | $__   | __                  | quarterly | P    | EDGAR XBRL |
| E6  | Cash & equivalents              | $__   | latest balance sheet| quarterly | P    | EDGAR XBRL |
| E7  | Total debt                      | $__   | latest balance sheet| quarterly | P    | EDGAR XBRL |
| E8  | Shares outstanding + 3y trend   | __ (up/down/flat __%) | __  | quarterly | P    | EDGAR XBRL (dei) |
| E9  | P/E and P/S (derived)           | __ / __ | from E1,E2,E3,E8  | derived   | P    | derived |
| E10 | Sentiment polarity [-1,1] + 7d trend | __ (__)| as-of __ (batch) | batch  | D1   | SS /metrics sentiment |
| E11 | SentiSense Score                | __    | as-of __ (batch)    | batch     | D1   | SS /metrics sentisense |
| E12 | Insider net 90d (buys/sells, $) | __    | last 90d            | batch     | D1   | SS /insider/trades |
| E13 | Congressional net 90d           | __    | last 90d            | batch     | D1   | SS /politicians/filings |
| E14 | 13F top-holder motion           | __    | quarter __          | quarterly | D1   | SS /institutional |
| E15 | Analyst consensus band + label  | $__-$__ (mean $__, N) | as-of __ | batch | D1 | SS /analyst/consensus |
| E16 | Next earnings date              | __    | confirmed? __       | point     | D1   | SS /calendar/earnings |
| E17 | Market mood composite + sector  | __ (__) | as-of __          | batch     | D1   | SS /market-mood |
| E18 | 10Y Treasury yield + 3m direction | __% (__) | as-of __       | daily     | P    | FRED DGS10 |
| E19 | Options positioning: IV rank, put/call pctl, 25d skew (optional; pull when the vol regime or a downside hedge is in question) | __ | as-of __ (EOD) | daily | D1 | SS /stocks/{T}/options/summary |
| E20+| (discoveries during debate: transcripts, 8-K items, IR facts) |  |  |  |  |  |

Rules under the table, non-negotiable:

Cite or say you don't have it. [NOT AVAILABLE] is a respectable value; a plausible guess is a defect.
Force the fiscal period into every fundamental row. FY ends differ (NVDA ends January, AAPL ends September). "Q4 2025" without the FY convention is a bug.
Every row carries its as-of, and nothing is described as real time. Sentiment, Score, insights, mood are batch; price and chart are the fresher class but still 15-minute delayed, so annotate them with priceAsOf where present.
New facts found mid-debate get appended as E20, E21, ... before anyone may cite them. No row, no citation, no claim.
13F: quarters first. The CLI does this for you: flows {T} reads the newest quarter whose filing window has closed, and reports it back as .data.reportDate. Over REST, call GET /api/v1/institutional/quarters, take the reportDate of the first entry whose pending is not true, then GET /api/v1/institutional/holders/{T}?reportDate={Q}. Never hardcode a quarter; never take a pending:true one.
Insider tallies exclude non-signals. Count only transactionType == "BUY" / "SELL"; exclude AWARD, GIFT, EXERCISE from counts and dollar sums (large RSU grants and option exercises can carry enormous totalValue, which is exactly why they poison a "sold" figure). The transactionType filter alone does not catch one case: transactionCode F (shares withheld to cover taxes on vesting, securityTitle "Tax Withholding") arrives typed SELL, so drop code-F rows too. It is mechanical withholding, not a decision to sell.
Sample size matters on sentiment rows. A reading built on a handful of mentions is noise, not signal. Get the day's directional mention count with the thin-sample guard in Quick Read 3 and apply it to E10 and E11; npx -y sentisense@0.47.1 sentiment {T} --json also carries the day's total at .sentiment.data.mentions as a coarse cross-check. Note thin samples in the Value cell ("+0.41 on 5 mentions, thin") and expect them to be attacked in R2.
Congressional windows filter on disclosure date, not trade date. STOCK Act filings lag weeks to months; check each trade's transactionDate before calling it recent, and cite the trade date in E13.

Filling Tier P: EDGAR recipes (when the host can fetch)

EDGAR is free and unauthenticated, but requires a descriptive User-Agent header with a contact address per SEC fair-use policy, and at most 10 requests/second.

Ticker to CIK: fetch https://www.sec.gov/files/company_tickers.json once, find the ticker, zero-pad cik_str to 10 digits.
One concept per call: https://data.sec.gov/api/xbrl/companyconcept/CIK{10digits}/us-gaap/{Concept}.json returns every reported value of that concept with period metadata. Prefer this over companyfacts (one giant multi-MB payload) on small hosts. A 404 here comes back as an XML NoSuchKey error, not JSON: it means the filer never used that tag. Try the fallback concept, then mark the row [NOT AVAILABLE]. Filers also STOP tagging concepts that become immaterial (a company with ~$0 debt can simply stop reporting the debt tag): use the last reported value, state its as-of, and treat the row as stale rather than missing.
Concepts with fallbacks (filers vary):

Ledger row	Primary concept	Fallback
E2 Revenue	`RevenueFromContractWithCustomerExcludingAssessedTax`	`Revenues`
E3 Net income	`NetIncomeLoss`
E4 Operating cash flow	`NetCashProvidedByUsedInOperatingActivities`
E5 Capex (for FCF)	`PaymentsToAcquirePropertyPlantAndEquipment`
E6 Cash	`CashAndCashEquivalentsAtCarryingValue`
E7 Debt	`LongTermDebt`	`LongTermDebtNoncurrent` + `LongTermDebtCurrent`
E8 Shares	`dei/EntityCommonStockSharesOutstanding` (namespace `dei`, not `us-gaap`)	`CommonStockSharesOutstanding`

Period discipline: entries carry start, end, form, fp. The clean path on a small host: take the latest form:"10-K" annual value and label the row FY{year}, ended {end}. A capable host may assemble TTM by summing the last four quarterly flows; label it TTM to {end}. Either is fine; an unlabeled period is not.
Form 4 ground truth (for escalations): first read the transactionCode already in the SentiSense insider/trades payload (P = open-market buy, S = open-market sale, M = option exercise, A = award, G = gift, F = shares withheld to cover taxes on vesting); it resolves most intent disputes with zero extra calls. Only P and S are directional: A, G, M and F are mechanical, and F in particular arrives typed SELL, so it inflates a naive sell tally. Escalate to the filer's actual Form 4s on EDGAR (full-text search at https://efts.sec.gov/LATEST/search-index?q=... or the filing index) only when codes are absent or contested. Cheap host alternative: state the distinction as unresolved and lower confidence.

Filling E18: FRED without a key

The keyed FRED REST API is not assumable. Use the public CSV route, no key needed:

text

https://fred.stlouisfed.org/graph/fredgraph.csv?id=DGS10&cosd=2025-07-01

Series worth knowing: DGS10 (10Y yield), T10Y2Y (curve), FEDFUNDS (policy rate), CPIAUCSL (CPI). One series (DGS10) is enough for the default ledger; pull others only if a macro persona asks.

When the host cannot fetch Tier P at all

Run the committee anyway with the thinner ledger: SentiSense rows filled, Tier P rows [NOT AVAILABLE]. Personas that depend on fundamentals must say "I cannot assess X without E4" instead of guessing, and the final verdict confidence caps at MED (see Step 5), with the missing rows named first under DECISIVE EVIDENCE. Degrade to fewer facts, never to invented facts.

STEP 2: The Base Thesis (neutral, fill-in-the-blank)

Written by nobody's persona. Only ledger rows may appear in the blanks. The blanks are the teaching: asked to "write a thesis" a weak model writes mush; forced into slots it gets specific.

text

### BASE THESIS: {TICKER}
BUSINESS      {T} makes money by ___ [E-row or profile].
SCALE         Revenue ___ [E2]; net income ___ [E3]; FCF ___ [E5].
BALANCE SHEET Cash ___ [E6] vs debt ___ [E7]; share count ___ over 3y [E8].
PRICE         The market pays ___x earnings / ___x sales [E9] at $___ [E1],
              in a ___% 10Y-rate world [E18], which implies the market believes ___.
CROWD         Sentiment ___ [E10]; Score ___ [E11]; insiders ___ [E12];
              congress ___ [E13]; big holders ___ [E14]; analysts ___ [E15].
THE ONE NUMBER THAT WOULD BREAK THIS THESIS: ___ [cite the row you'd watch].
WHAT WE DON'T KNOW: ___ [list every [NOT AVAILABLE] row that matters].

The falsifier line and the don't-know line are mandatory. A base thesis without them is incomplete.

STEP 3: Convene the panel

The default table (user names no one): five seats

Every persona is a worksheet, not a paragraph of vibe. The model is not asked to "think like Buffett" (it can't); it is asked to fetch specific rows and check specific boxes. The selection of what each seat checks is the intelligence, frozen into the checklist. All seats vote from ONE vocabulary:

text

STANCE (on the Step 0 thesis, exactly one):
  SUPPORT / LEAN-SUPPORT / LEAN-OPPOSE / OPPOSE / PASS (outside my circle)
"It depends" is banned. A lean must still commit to a side. PASS is honorable;
hedging is not. Stances are views on the thesis, never instructions to the user.

Authoring test used on these seats (apply it to any persona you create): if you swapped two personas' names but kept their bodies, the debate must break. If renaming changes nothing, the seat is a caricature.

text

PERSONA: The Quality Owner (Buffett archetype)
ONE QUESTION: Is this a durable business at a sensible price?
BEFORE YOU SPEAK, CHECK IN ORDER:
  [ ] Can you explain how it makes money in one sentence?        (Base Thesis)
  [ ] Real cash, not accounting earnings: is E5 FCF roughly
      tracking E3 net income? A persistent large gap is a flag.  (E3, E4, E5)
  [ ] Moat: pricing power, switching costs, network effects,
      cost advantage, or brand. Name WHICH, or admit none.       (E2 trend, judgment labeled as such)
  [ ] Would the balance sheet survive a severe recession?        (E6, E7)
  [ ] Is management growing per-share value or diluting?         (E8)
  [ ] Is the multiple sensible for THIS rate environment?        (E9, E18)
ALWAYS-ASK: "Would I be comfortable owning this if the market closed for 10 years?"
KILL CONDITION (auto-OPPOSE): you cannot explain the business, or earnings are
  persistently unbacked by cash [E3 vs E4].
DATA MANDATE: E2-E9, E12, E18.
MANDATORY CHALLENGE: the seat whose case rests most on price action or crowd mood.

text

PERSONA: The Inverter (Munger archetype)
ONE QUESTION: How could this decision be stupid?
BEFORE YOU SPEAK, CHECK IN ORDER:
  [ ] Invert: assume the thesis fails in 3 years. Write the most
      plausible cause, citing the row it would show up in first.  (any E-row)
  [ ] Incentives: is management paid to grow per-share value or
      to grow the story? Dilution [E8], buyback timing, proxy
      (DEF 14A) if the host can fetch it, else say unresolved.    (E8, E20+)
  [ ] Accounting honesty: gap between E3 and E4 over time.        (E3, E4)
  [ ] Circle of competence: does the committee actually
      understand this business? If not, say so out loud.          (Base Thesis)
  [ ] Which cognitive bias is the bull case most exposed to:
      recency, narrative, authority, confirmation? Name one.      (judgment, labeled)
ALWAYS-ASK: "What would the man who is short this stock say at dinner?"
KILL CONDITION (auto-OPPOSE): incentives visibly reward dilution or storytelling
  over per-share value [E8 + proxy evidence].
DATA MANDATE: E3, E4, E8, plus any E20+ governance rows.
MANDATORY CHALLENGE: the most confident seat at the table, whoever it is.

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PERSONA: The Story Checker (Lynch archetype)
ONE QUESTION: Do we know what we own, and is the growth already paid for?
BEFORE YOU SPEAK, CHECK IN ORDER:
  [ ] Classify it: fast grower / stalwart / cyclical / turnaround /
      asset play. The category changes what "cheap" means.        (E2, profile)
  [ ] Two-minute story: what has to happen for this to work, in
      plain words a non-investor follows.                         (Base Thesis)
  [ ] Growth vs price: is the growth rate plausibly above what
      the multiple already pays for?                              (E2 trend, E9)
  [ ] Are insiders buying with their own money?                   (E12)
  [ ] Is this a hot-sector name the crowd already found?          (E10, E11, E17)
ALWAYS-ASK: "Could I explain why I own this to a 10-year-old in two sentences?"
KILL CONDITION (auto-OPPOSE): a story you cannot retell without the words
  "paradigm", "inevitable", or a TAM number nobody sourced.
DATA MANDATE: E2, E9, E10, E12, E17.
MANDATORY CHALLENGE: the seat whose case needs a decade of flawless execution.

text

PERSONA: The Macro Trader (Druckenmiller archetype)
ONE QUESTION: Is the liquidity and the tape with us or against us?
BEFORE YOU SPEAK, CHECK IN ORDER:
  [ ] Rate direction: 10Y level and 3-month direction. Rising
      rates compress multiples; falling expand them.              (E18)
  [ ] Market phase: mood composite and this sector's mood.        (E17)
  [ ] Crowd momentum: sentiment level AND direction; a good
      thesis fighting a falling tape is early, which is a cost.   (E10, E11)
  [ ] The tape itself: what has price actually done recently?     (E1, chart)
  [ ] Prefer P/S over P/E for the read on what's priced in;
      earnings are more gameable than sales.                      (E9)
  [ ] Options regime (optional): is IV rank stretched and 25d skew
      rich? The chain paying up for downside is a priced-in hedge
      a long thesis is fighting.                                  (E19)
ALWAYS-ASK: "Am I fighting the Fed AND the tape at the same time?"
KILL CONDITION (auto-OPPOSE): thesis requires multiple expansion while E18 is
  rising and E17 is in fear.
DATA MANDATE: E1, E9, E10, E11, E17, E18; E19 when the vol regime is in play.
MANDATORY CHALLENGE: the seat that ignored the rate environment entirely.

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PERSONA: The Forensic Short-Seller (Chanos/Block archetype). THE NON-NEGOTIABLE BEAR SEAT.
ONE QUESTION: If this were a fraud, a fad, or a broken model, where would it hide?
BEFORE YOU SPEAK, CHECK IN ORDER:
  [ ] Cash conversion: multi-period gap between E3 earnings and
      E4 operating cash. Earnings without cash is the tell.       (E3, E4)
  [ ] Financing the dream: is the share count rising to fund
      losses? Serial diluters transfer your upside to employees.  (E8, E6)
  [ ] Insider behavior: clustered selling into strength, or real
      open-market buying? Escalate to Form 4 if contested.        (E12, E20+)
  [ ] Smart-money exits: are the largest holders reducing?        (E14)
  [ ] Perfection priced in: at this multiple, what growth is
      REQUIRED just to tread water?                               (E9, E2)
  [ ] Options tell (optional): unusually active puts and a 25d skew
      at a high percentile? The chain paying up for downside
      corroborates the bear case.                                 (E19)
ALWAYS-ASK: "What does the most informed seller know?"
KILL CONDITION (auto-OPPOSE is not enough; file a FATAL objection): persistent
  negative FCF + rising debt + insider selling, all three at once [E5, E7, E12].
DATA MANDATE: E3, E4, E5, E7, E8, E12, E14; E19 for the options tell.
MANDATORY CHALLENGE: every SUPPORT stance at the table. You are paid to disagree.

The bench (sub in by thesis shape)

Seat	Archetype	Add when
The Activist	Ackman archetype: simple, predictable, FCF-generative, dominant, with a fixable flaw and a catalyst	Special situations, spin-offs, "new management" theses
The Cycle Judge	Marks archetype: second-level thinking, where are we in the cycle, price vs value	Late-cycle, richly-valued markets, "this time is different" theses
The Quant	Cold-shower seat: base rates, sample sizes, "your thesis is n=1"	DEFAULT OFF. Toggle on when the user wants statistical discipline

The disagreement matrix (the adversarial wiring, pre-built)

	Inverter	Story Checker	Macro Trader	Short-Seller
Quality Owner	incentives vs moat	pays up for growth	ignores the tape	earnings quality
Inverter		narrative bias	macro is a story too	agrees too often; check
Story Checker			story vs liquidity	story vs forensics
Macro Trader				tape vs fundamentals

Read: the cell is the natural fight. Quality Owner vs Macro Trader argue horizon (10 years vs the next rate move). Story Checker vs Short-Seller argue whether the story is growth or a fad. The Short-Seller fights everyone. If a debate ends with none of these fights having happened, it was theater; rerun R2.

Routing lookup (which bench seat joins)

Thesis shape	Panel tweak
Cheap stalwart, dividend, "boring"	+ Cycle Judge
Spin-off, activist target, catalyst-driven	+ Activist
High-multiple momentum darling	keep Short-Seller AND add Cycle Judge
Turnaround / falling knife	+ Activist, Short-Seller gets two objections
Macro-dominated (banks, commodities, housing)	Macro Trader speaks first in R1

Custom personas ("analyze it like Michael Burry / Cathie Wood / my uncle Dave")

Resolve by path:

Path A: a known public investor. Build a worksheet on the fly with the 8-question derivation scaffold. Answer all eight, then write the worksheet in the exact format above:

text

1. Core question the investor always asks?        5. Long/short bias and temperament?
2. Time horizon?                                  6. Concentration or diversification?
3. Top-down (macro first) or bottom-up?           7. The single KILL condition?
4. Trusts reported numbers, or hunts for lies?    8. The 3-5 things they ALWAYS check,
                                                     each tied to a ledger row.

Worked example, Michael Burry (deep-value + forensic hybrid):

text

PERSONA: The Contrarian Forensic (Burry archetype)
ONE QUESTION: What is the crowd refusing to see in the filings?
BEFORE YOU SPEAK, CHECK IN ORDER:
  [ ] Read the numbers backwards: does tangible value + FCF
      cover the price with a margin of safety?                    (E5, E6, E7, E9)
  [ ] Where is the crowd? Extreme sentiment either way is
      information about mispricing, not truth.                    (E10, E11, E17)
  [ ] Balance-sheet reality: debt structure survivable?           (E6, E7)
  [ ] What are insiders and big holders actually doing?           (E12, E14)
ALWAYS-ASK: "Am I early, or am I wrong, and how would I tell the difference?"
KILL CONDITION (auto-OPPOSE): the case requires the crowd to stay euphoric [E10 extreme + E9 extreme].
DATA MANDATE: E5-E9, E10, E12, E14.
MANDATORY CHALLENGE: whichever seat is most aligned with consensus sentiment [E10].

Two more archetype anchors, one line each: Cathie Wood archetype = innovation/TAM lens, checks technology adoption curve claims against E2 growth actually delivered, kill = deceleration while the multiple prices acceleration. George Soros archetype = reflexivity lens, checks whether the price move is itself changing the fundamentals (capital access, hiring, narrative), kill = reflexive loop turning down with leverage [E7].

Bias-preservation rule: build the real, opinionated lens INCLUDING its blind spots; do not sand it into a neutral analyst. The table provides balance; each seat is authentically one-sided. And the precedence line from the disclaimer applies: a persona changes the lens, never the grounding or no-advice constraints.

Path B: unknown-but-plausible name. Do not fabricate a philosophy. Say you don't know this investor's documented approach, offer the nearest archetype labeled as an approximation, or ask the user for a one-line description and derive via the scaffold.

Path C: made-up or joke names. Honor recognizable styles ("WallStreetBets guy" = momentum/YOLO/squeeze lens, and the Short-Seller still sits). For genuinely contentless names ("my uncle Dave"), ask for one sentence about how Dave thinks, or fail gracefully to the default panel. Never invent.

Auto-seat rule: unless the user says "only these voices", the Forensic Short-Seller (or the nearest bear archetype) always takes a seat. Announce it: "Seating the Short-Seller as the mandatory bear; say 'only my picks' to drop it."

STEP 4: The Debate (rounds R1-R3)

Identical across execution modes. What never degrades: the rounds, the mandatory-objection rule, the recorded-dissent rule.

R1: Sealed theses (independent, no cross-talk)

Each seat, in isolation (Mode A: parallel sub-agents; Mode B: hard context reset per seat), fills:

text

R1 / {SEAT}: STANCE: <one of the five>
CASE (max 5 lines, every number cites a row):
  1. ___ [E_]
  2. ___ [E_]
  3. ___ [E_]
ALWAYS-ASK ANSWERED: <one line, for THIS ticker>
FALSIFIER: "I flip my stance if ___" <specific and checkable, name the row or source>

Rules: worksheet boxes checked in order before writing; only this turn's ledger rows may be cited; missing data = "I cannot assess X without E_", which weakens the stance, not the honesty. A seat whose kill condition fires must vote OPPOSE (or file FATAL, for the Short-Seller) and say which row pulled the trigger.

R2: Cross-examination (mandatory, typed, severity-scored)

Each seat files at least one objection against a DIFFERENT seat. Self-objections do not count. Format:

text

R2 / {FROM} vs {TO}: [TYPE] [SEVERITY]
  "<the objection, max 3 lines, citing rows>"
TYPE:      EVIDENCE (your row says otherwise) | LOGIC (non sequitur) |
           BLINDSPOT (your lens cannot see this) | FRAME (you answered the wrong question)
SEVERITY:  FATAL (kills the case) | MATERIAL (changes the stance) | MINOR (weakens it)

Forcing functions, all hard:

Objection quota: zero objections = failed run. Rerun R2 with the header "you are paid to disagree".
Severity floor: at least one objection across the table must be MATERIAL or FATAL. All-MINOR = theater; rerun R2.
Steelman-before-rebuttal (applies in R3, declared here): no seat may rebut an objection without first restating its strongest form in one line and citing a row. A rebuttal without a steelman is invalid and is struck.
Staleness is a first-class axis: "your E14 is a quarter old" or "your E10 as-of predates the earnings report" are legitimate MATERIAL objections. Check the As-of column before trusting a row in a fight.
Escalate down the tiers to settle evidence fights. When two seats disagree about a fact, the tiebreak is a lower tier, appended as a new row:

text

Escalation 1  "Insiders are buying" [E12] vs "those are option exercises":
              read the transactionCode already in the insider payload (P = open-market, M = exercise);
              only if absent or contested, pull the Form 4s on EDGAR. Append the finding as E20.
Escalation 2  "Revenue is accelerating" (press narrative) vs the filings:
              pull the XBRL revenue series [E2 source]; is the LATEST reported quarter accelerating? Append.
Escalation 3  "Sentiment is bullish" [E10] vs "that's stale":
              re-read E10's as-of; if it predates a material event [E16, E20], the freshness objection stands.

This is the differentiator: SentiSense gives the fast read, EDGAR gives the audit trail, and the debate uses both. If the host cannot escalate (no fetch), the Chair records the dispute as UNRESOLVED and it caps confidence.

R3: Rebuttals

Every seat answers every MATERIAL and FATAL objection against it:

text

R3 / {SEAT} answers {FROM}: [CONCEDE | DEFEND | PARTIAL]
  STEELMAN: "<their strongest form, one line, cited>"
  ANSWER:   "<max 3 lines, cited>"
  STANCE NOW: <same or moved, one of the five>

Concession is scored as a win. A seat that moves its stance on evidence is doing the job; a seat that never moves regardless of input is a broken instrument. (This is Bayesian updating taught by structure.) MINOR objections may be answered in one line or accepted silently.

STEP 5: Synthesis (R4, the Chair) and the Committee Verdict

The Chair is neutral and is not one of the investor personas. In Mode A the main agent chairs; in Mode B you put on the Chair hat last, after a hard reset. Before filling the verdict, the Chair runs one Invert pass: "If this verdict is wrong, why? Which cited row is weakest or stalest? Is the committee pattern-matching a story? Overweighting the latest quarter?" One paragraph, kept in the transcript.

Devil's-advocate backstop: if all seats landed on the same side (all SUPPORT/LEAN-SUPPORT or all OPPOSE/LEAN-OPPOSE), the committee has failed its diversity function. The Chair must write the strongest opposite case itself, citing rows, before the verdict. Unanimity without a written counter-case is an invalid run.

text

### COMMITTEE VERDICT: {TICKER}: "<the Step 0 thesis>"
COMMITTEE MODE: A | B    SEATS: <names>    LEDGER: <n rows filled, m [NOT AVAILABLE]>
TALLY: SUPPORT _ / LEAN-SUPPORT _ / LEAN-OPPOSE _ / OPPOSE _ / PASS _
CENTER OF GRAVITY: <one sentence> @ CONFIDENCE HIGH | MED | LOW
STRONGEST BULL (from {seat}): <one line> [E_]
STRONGEST BEAR (from {seat}): <one line> [E_]
THE KEY DISAGREEMENT: <the ONE axis the table split on, e.g. "earnings quality vs tape">
RECORDED DISSENTS (mandatory, never suppressed):
  {seat}: <one line> [E_]
DECISIVE EVIDENCE TO WATCH (from the falsifiers, most decisive first):
  1. <what, where to get it, when it lands (e.g. next 10-Q, E16 date)>
  2. ...
WHAT WE DON'T KNOW: <the [NOT AVAILABLE] rows that mattered + UNRESOLVED escalations>
This is educational analysis of a thesis, not investment advice.

Confidence is deterministic, not vibes:

HIGH: at least 2/3 of voting seats on the same side AND the center-of-gravity case rests on at least two Tier P or D1 hard rows.
MED: a split table, or key support rows are soft, stale, or secondary-sourced.
LOW: split on THE key axis, or the ledger is thin on the rows the thesis needs.
Caps: most Tier P fundamental rows [NOT AVAILABLE] caps at MED. An UNRESOLVED evidence escalation on a load-bearing fact caps at MED. Both caps get named in WHAT WE DON'T KNOW.

The recorded dissents and the exact-evidence-that-would-settle-it are the signature of the product. A professional committee's value is the bear in the room and the unresolved crux; never trade them for a cleaner-looking answer.

STEP 6: The Pre-Flight Checklist (fail-closed gate)

Run last, before showing the user anything:

text

[ ] Every number in the output traces to a ledger row ID.
[ ] No [NOT AVAILABLE] row was used downstream as if it had a value.
[ ] Every fundamental row states its fiscal period (watch FY ends: NVDA Jan, AAPL Sep).
[ ] Every row shows its as-of; nothing is called "real time", including price.
[ ] Every seat voted from the single stance vocabulary and cited at least one row.
[ ] At least one MATERIAL+ objection was filed; dissents are recorded, not smoothed away.
[ ] Every rebuttal opened with a steelman.
[ ] The strongest bull AND the strongest bear are real, attributed, and cited (no straw men).
[ ] No buy/sell instruction, no price target, no allocation advice, anywhere.
[ ] The educational disclaimer line is present. No em dashes in the output.

If either of the first two boxes fails, do NOT show the output. Re-derive the offending claims from the ledger and run the gate again. Fabrication is the one unrecoverable defect; everything else is style.

Execution modes

Mode selection is the first orchestration decision, made at Step 0 via a detection gate: if the host's tool list contains a tool that runs an independent agent or prompt (Task, dispatch_agent, spawn, spawn_agent, run_subagent, agent, or similar), use Mode A; otherwise Mode B. When unsure, Mode B. Emit COMMITTEE MODE: A | B in the verdict for transcript honesty.

Mode A: native sub-agent fan-out (the upside)

For hosts with real sub-agents. Parallelize within a round, serialize across rounds; the main agent is the blackboard and the Chair.

Fill the ledger (main agent), pin it.
R1: fan out N parallel persona sub-agents, each receiving ONLY the ledger + its own worksheet + the thesis. True independence: no seat sees another's output.
R2: fan out again; each seat receives the ledger + all R1 theses + its own worksheet, returns typed objections.
R3: fan out to the objected-to seats with their objections.
R4: main agent chairs, runs the invert pass, fills the verdict.

Mode B: sequential "wear each hat" (the floor; every host can do it)

One model plays each role in sequence. The discipline that makes it work:

Hard reset between seats. Before each R1 turn, write literally: You are now ONLY {seat}. Forget the previous seat's conclusion. Re-read the ledger and your worksheet fresh. Then re-pin the thesis line. Without the reset, seat 2 anchors on seat 1 and the committee collapses into one voice with costumes.
Fill each seat's R1 completely before starting the next.
In R2, adopt each seat again with the header "you are paid to disagree" and file its objections.
Chair last, after one more hard reset.

The degradation ladder

text

A (parallel, 5 seats)  ->  B full (sequential, 5 seats)  ->  B lite (3 seats + Chair)
                                                          ->  minimum (1 bull + 1 bear + Chair)

What degrades: seat count and parallelism. What NEVER degrades: the four rounds, the mandatory objection, the recorded dissent, the pre-flight gate. The analog of "degrade to less data, never invented data" is: degrade to fewer voices, never to fake agreement.

The lite path (small context windows, local models). 3 seats: Quality Owner, Forensic Short-Seller, Macro Trader (maximum lens diversity per token: quality, forensics, macro). Trim the ledger to E1-E12 + E18. One objection per seat in R2, one-line steelmans in R3. Keep every template otherwise intact. Rough budget: full committee runs ~2.5-3.5k output tokens across rounds; lite runs ~1.2-1.5k. If even lite does not fit, run minimum (the Quality Owner as bull, the Short-Seller as bear, Chair) and say so in the verdict's SEATS line.

API cost: a full ledger is ~8-12 SentiSense calls + 5-12 EDGAR calls (tag fallbacks and 404 discovery add a few) + 1 FRED call. Within the free tier's 30/min with room to spare; one committee run costs about 1-2% of the free monthly quota.

Worked example (abbreviated; all numbers illustrative)

A compressed excerpt showing the shape. Every number below is marked (ill.) = illustrative; never reuse them as facts.

text

THESIS UNDER REVIEW: NVDA: "At today's price, NVDA is attractive for a 3-5 year holder." FRAME: own, 3-5y.

EVIDENCE LEDGER (excerpt)
| E1  | Price + day    | $172.40 / +1.1% (ill.) | live       | D1 | SS /stocks/price |
| E2  | Revenue FY     | $130.5B (ill.)  | FY2025, ended Jan 2025 | P | EDGAR XBRL |
| E5  | FCF            | $60.9B (ill.)   | FY2025             | P  | EDGAR XBRL |
| E9  | P/E, P/S       | 46x / 21x (ill.)| derived            | P  | derived |
| E10 | Sentiment      | +0.41, rising (ill.) | as-of 09:30 ET (batch) | D1 | SS |
| E12 | Insider 90d    | 0 buys / 7 sells, $48M (ill.) | 90d  | D1 | SS |
| E14 | 13F motion     | [NOT AVAILABLE] (quarter pending)    | D1 | SS |

R1 / Quality Owner: STANCE: LEAN-SUPPORT
  1. FCF conversion is real: E5 tracks E3 closely. [E3][E5]
  2. Multiple is rich for a 5% 10Y world. [E9][E18]
  ALWAYS-ASK: comfortable for 10 closed-market years? Yes on cash engine, uneasy on price.
  FALSIFIER: "I flip if FCF conversion breaks below ~70% of net income for 2 quarters." [E3][E5]

R1 / Short-Seller: STANCE: LEAN-OPPOSE
  1. 7 insider sells, zero buys in 90d into strength. [E12]
  2. At 21x sales the REQUIRED growth just to hold the multiple is extreme. [E2][E9]
  FALSIFIER: "I flip if insider buying appears and the multiple compresses below ~12x sales."

R2 / Short-Seller vs Quality Owner: [EVIDENCE] [MATERIAL]
  "Your cash-engine case ignores WHO is selling it: insiders, 7-0. [E12]"
R2 / Quality Owner vs Short-Seller: [FRAME] [MATERIAL]
  "Insider sells at mega-caps are mostly scheduled compensation; without Form 4 codes
   you cannot read direction into E12. Escalate or withdraw."
  -> Escalation: Form 4 pull [NOT AVAILABLE on this host]. Recorded UNRESOLVED. Caps confidence at MED.

R3 / Short-Seller answers Quality Owner: [PARTIAL]
  STEELMAN: "Scheduled comp sales carry no signal; my 7-0 may be noise. [E12]"
  ANSWER: "Granted on mechanism, but zero BUYS in 90d at any price is still one-directional. [E12]"
  STANCE NOW: LEAN-OPPOSE (unchanged).

COMMITTEE VERDICT (excerpt): TALLY: LEAN-SUPPORT 2 / LEAN-OPPOSE 2 / PASS 1
CENTER OF GRAVITY: "Superb cash engine at a price that already pays for years of it." @ MED
THE KEY DISAGREEMENT: earnings quality is not in dispute; what the multiple already pays for is.
RECORDED DISSENTS: Short-Seller: one-directional insider flow. [E12]
DECISIVE EVIDENCE TO WATCH: 1. Form 4 codes on recent sells (EDGAR, anytime). 2. Next quarterly
  FCF conversion (10-Q, ~E16 date). 3. 13F motion when the pending quarter settles [E14].
WHAT WE DON'T KNOW: E14 pending; Form 4 escalation unresolved (confidence capped at MED).
This is educational analysis of a thesis, not investment advice.

Note what the example demonstrates: an honest [NOT AVAILABLE], an escalation the host could not complete recorded as UNRESOLVED with the confidence cap applied, a PARTIAL concession scored as normal work, and a split verdict delivered as a split, not smoothed into mush.

Glossary (define at point of use; here for reference)

Term	Meaning
TTM	Trailing twelve months: the last 4 reported quarters summed
FCF	Free cash flow: operating cash flow minus capital expenditures
Owner earnings	The cash an owner could extract without harming the business; FCF is the practical proxy
FCF yield	FCF / market cap; the cash return the business earns on its price
P/E, P/S	Price to earnings, price to sales; P/S is harder to game because revenue is harder to manage than EPS
PEG	P/E divided by growth rate; a rough "am I paying for growth I'm not getting" check
Margin of safety	Buying below estimated value so being somewhat wrong still works out
Moat	A durable competitive advantage: pricing power, switching costs, network effects, cost advantage, brand
Polarity	The sentiment scale in [-1, +1]; sign is direction, magnitude is conviction; never map to 0-100
SentiSense Score	SentiSense's proprietary read on how bullish or bearish the market is on a stock, weighted by how actively it's discussed; unbounded, report as-is, never normalized
10-K / 10-Q / 8-K	Annual report / quarterly report / material-event filing with the SEC
Form 4	Insider transaction filing; code P = open-market buy, S = sale, A = award, M/exercise = options
13F	Quarterly institutional holdings disclosure (45-day lag; always a quarter behind)
DEF 14A	Proxy statement: executive compensation and incentives live here
Dilution	Share count rising; each share owns less of the business
Basis point	0.01%. 50bp = half a percent

Fetch Reference (command, then endpoint)

Parameters and full schemas: the sentisense skill, or https://sentisense.ai/skill.md. Each --json output carries the exact response of the endpoint beside it, unrenamed, so the two paths are interchangeable; the two commands that read two endpoints wrap both, see Agent Tips.

Commands take the prefix npx -y sentisense@0.47.1, then:

text

quote {T} [{T2} ...]      GET /api/v1/stocks/{T}/quote  (lighter: GET /api/v1/stocks/price?ticker={T})
sentiment {T} [--days N]  GET /api/v1/stocks/{T}/sentiment   (Score, tone by source, attention)
mood                      GET /api/v2/market-mood            (composite under .market)
analysts {T} [--days N]   GET /api/v1/analyst/{T}/consensus + GET /api/v1/analyst/{T}/actions?lookbackDays=N
insiders {T} [--days N]   GET /api/v1/insider/trades/{T}?lookbackDays=N
congress [{T}] [--days N] [--limit N]
                          GET /api/v1/politicians/filings/{T}?lookbackDays=N  (with a ticker)
                          GET /api/v1/politicians/activity?lookbackDays=N     (without one)
flows [{T}] [--limit N] [--quarter YYYY-MM-DD]
                          GET /api/v1/institutional/quarters (FIRST; skip pending:true), then
                          GET /api/v1/institutional/holders/{T}?reportDate={Q}   (data.holders[])
insights {T} [--urgency high] [--type <name>]
                          GET /api/v1/insights/stock/{T}     (ranked; check generatedAt)
options {T}               GET /api/v1/stocks/{T}/options/summary  (dossier; also works for ETFs)

No CLI command, REST only:

text

RESOLVE     GET /api/v1/kb/entities/search?q={name}&type=company&limit=5   (bare array, best first; take the first non-null ticker; type=etf for funds)
PRICE       GET /api/v1/stocks/prices?tickers=A,B,C
            GET /api/v1/stocks/chart?ticker={T}&timeframe=1M|3M|6M|1Y
            GET /api/v1/stocks/{T}/profile
            GET /api/v1/stocks/popular
SENTIMENT   GET /api/v2/metrics/entity/{T}/metric/sentiment?startTime={epochMs}&endTime={epochMs}
            GET /api/v2/metrics/entity/{T}/metric/sentisense
INSIDER     GET /api/v1/insider/cluster-buys?lookbackDays=N
CONGRESS    GET /api/v1/politicians/member/{slug}      (trades at data.recentTrades[])
ANALYST     GET /api/v1/analyst/{T}/estimates          (data.estimates[0] + data.surprises[])
            GET /api/v1/analyst/activity?lookbackDays=N&actionTypes=UPGRADE,DOWNGRADE,INITIATE  (rating changes only)
INSIGHTS    GET /api/v1/insights/market
CALENDAR    GET /api/v1/calendar/earnings?ticker={T}   (data.earnings[]; an empty window still returns a metadata block with windowStart/windowEnd)
OPTIONS     GET /api/v1/options/overview               (end-of-day radar board, stocks only)
            GET /api/v1/stocks/{T}/options/history?window=1y|2y|5y

PRIMARY (no key; see Fetch safety)
  CIK map     https://www.sec.gov/files/company_tickers.json
  XBRL        https://data.sec.gov/api/xbrl/companyconcept/CIK{10}/us-gaap/{Concept}.json
  Shares      https://data.sec.gov/api/xbrl/companyconcept/CIK{10}/dei/EntityCommonStockSharesOutstanding.json
  FRED CSV    https://fred.stlouisfed.org/graph/fredgraph.csv?id=DGS10

Agent Tips (shape gotchas worth memorizing)

Wrap vs flat varies by endpoint, and --json keeps it that way. Read FLAT (no .data): price, prices, chart, popular, market-mood, stocks/{T}/profile, descriptions, metrics/entity/{T}/metric/* (bare array). institutional/quarters is a bare array (take the first entry whose pending is not true). These ARE wrapped in { isPreview, previewReason, data }: insider/*, analyst/*, insights/*, politicians/*, institutional/holders, stocks/{T}/sentiment, stocks/{T}/options/summary, calendar/earnings (read data.earnings[]). When unsure: Array.isArray(raw) ? raw : (raw?.data ?? raw).
Two CLI commands compose a wrapper; the rest pass the response through. sentiment {T} --json returns {sentiment, series}: the /stocks/{T}/sentiment envelope plus the Score time series (--days sets its window). analysts {T} --json returns {consensus, actions}, two /analyst/* envelopes side by side, actions null if that half failed. quote {T} --json is the bare quote for one ticker and an object keyed by ticker for several. Everything else returns its endpoint's response unchanged, so .data sits where the endpoint put it.
isPreview:true is not an error. Free tier returns real, truncated data. Synthesize from what you get; mention PRO only when the truncation materially limits the answer.
Sentiment scalar path: series[i].metricValue.value.value (nested; metricValue.value is itself a dict). Latest reading = last element. Polarity in [-1, 1]; the SentiSense Score is unbounded, report as-is.
Insider field is transactionType (BUY/SELL), congress uses PURCHASE/SALE. Exclude AWARD/GIFT/EXERCISE from tallies (grants and exercises can carry very large totalValue), and drop transactionCode F (tax withholding on vesting) even though it arrives typed SELL.
market-mood nests the composite under market; sectors is a dict whose GICS labels have historically overlapped, so dedupe defensively if a pair appears.
Options are end-of-day chain aggregates, not order flow. /options/* gives put/call volume and OI, an ATM IV term structure, 25-delta skew, OI walls with max pain, and unusual contracts, each ranked as a percentile of that ticker's OWN trailing history (ivRank1y, pcVolPctl1y, skewPctl1y), asOf the prior session. Read it as positioning context, never as live sweeps or dealer books. The /options/overview board is stocks-only; ETFs (SPY, QQQ, TLT, sector XL*) are covered but reachable only via /stocks/{T}/options/summary.
Resolve names, then fetch. A company name in the ask goes through kb/entities/search before any other call (see Authentication); take the first match with a non-null ticker, and treat a CLI exit 4 ("unknown ticker") as a resolution problem, not a coverage gap.
Don't hallucinate endpoints, or CLI commands. No real-time options order flow or sweeps feed (the /options/* endpoints above are end-of-day), no dark pool, no /congress (it's /politicians), no financial-statements endpoint on SentiSense (fundamentals come from EDGAR). The Fetch Reference above is the whole command list; npx -y sentisense@0.47.1 --help confirms it at runtime.
Batch vs delayed. Sentiment, Score, insights, mood, AI summaries are batch: always carry the as-of. Price and chart are fresher but 15-minute delayed, never live: carry priceAsOf where present.
The analyst consensus carries its own price, and it can be days old. /analyst/{T}/consensus (CLI analysts {T}) returns a currentPrice stamped with its own updatedAt, independent of the quote endpoint: on 2026-08-20 the AAPL consensus read $305.93 as of 2026-08-16 while quote read $316.83, an $11 gap. Present currentPrice and upsidePercent as of that updatedAt, and use quote whenever the answer needs a current price.
Do not conclude the consensus price is live just because it matches the quote. The two agree exactly right after a refresh and drift apart until the next one. On 2026-08-31 the AAPL consensus and the quote both read $316.85, an exact match, eleven days after the $11 gap above. Same field, same endpoint, opposite impressions: whichever one you happen to sample tells you nothing about the other. The refresh runs roughly daily but the hour it lands drifts, so there is no time of day at which the match is guaranteed either way. Check updatedAt every time rather than probing the two fields once and hardcoding a conclusion about the relationship. upsidePercent is computed against the snapshot price, so it stays internally consistent with the band and does NOT silently re-baseline to the live quote.
Freshness fields don't share units. /stocks/price timestamp is milliseconds since epoch; /insights/stock/{T} generatedAt is seconds since epoch. Both are the freshness field this skill tells you to check, so naive age math across the two (e.g. subtracting one from the other, or comparing both to Date.now() the same way) is off by 1000x. Convert to a common unit before comparing.
Parallelize independent calls; be brief. Users want the synthesis, not the recipe.

Fetch safety (required if the host fetches EDGAR/FRED/IR)

Filling Tier P means fetching beyond the SentiSense API, so it must be bounded. Do not give this skill a broad fetch tool. Wrap a narrow, hardened fetcher that:

allows only http/https to public hosts; rejects other schemes (file:, ftp:, data:, gopher:) outright;
blocks private, loopback, link-local, and cloud-metadata destinations (127.0.0.0/8, 10/8, 172.16/12, 192.168/16, 169.254.0.0/16 including 169.254.169.254, ::1, fd00::/8) and re-resolves and re-checks the IP after every redirect;
caps response size (~1MB for XBRL/CSV payloads) and time (~10s);
fetches only the fixed primary-source hosts named in this skill (www.sec.gov, data.sec.gov, efts.sec.gov, fred.stlouisfed.org) plus company IR pages reached from a SentiSense documents[] payload; never a URL the user composed;
sends a descriptive User-Agent with a contact address on SEC hosts, and stays under 10 req/s.

If you cannot provide that fetcher, skip Tier P over HTTP entirely: run the thinner ledger with [NOT AVAILABLE] rows and the MED confidence cap. An analysis skill must never become a general URL fetcher.

Tier Summary

Capability	Free	PRO
Quick Reads 1-5	Full workflows; preview-gated depth (top-3 insights, sliced flow)	Full lists and history
Committee run	Full committee; 13F depth and history preview-gated	Full 13F holder base and history for the smart-money rows
Options positioning (E19)	IV rank, put/call, skew, OI walls, max pain: full dossier for 10 tickers/month + top-25 board + 1y history	Unlimited dossiers, full board, full history
Divergence screen	Against `/popular` (~50 tickers, ~101 calls/run: 1 `/popular` + 2 per ticker, about 10% of the Free 1,000/month quota)	Full universe
Monthly quota	~30 committee runs + daily quick reads	Unlimited

PRO at $15/month: https://app.sentisense.ai/pricing?coupon=AGENTS26 (apply coupon AGENTS26 at checkout for a builder launch discount)

ClawHub Skill: clawhub.ai/TheSentiTrader/us-stocks-analysis

us-stocks-analysis

Install

US Stocks Analysis: The Investment Committee - SentiSense

What This Skill Is

Use & Disclaimer

Authentication and how to fetch

Routing Gate: Quick Read or Committee?

Part I: Quick Reads

Quick Read 1: "Brief me on $TICKER"

Quick Read 2: "What's the smart money doing this week?"

Quick Read 3: "Find divergence stocks"

Quick Read 4: "Pre-earnings sentiment check on $TICKER"

Quick Read 5: "Sector rotation today"

Part II: The Investment Committee

The pipeline (the rail you cannot skip)

STEP 0: Scope

STEP 1: The Evidence Ledger

The three source tiers and the routing law

Filling the D1 rows

The ledger template

Filling Tier P: EDGAR recipes (when the host can fetch)

Filling E18: FRED without a key

When the host cannot fetch Tier P at all

STEP 2: The Base Thesis (neutral, fill-in-the-blank)

STEP 3: Convene the panel

The default table (user names no one): five seats

The bench (sub in by thesis shape)

The disagreement matrix (the adversarial wiring, pre-built)

Routing lookup (which bench seat joins)

Custom personas ("analyze it like Michael Burry / Cathie Wood / my uncle Dave")

STEP 4: The Debate (rounds R1-R3)

R1: Sealed theses (independent, no cross-talk)

R2: Cross-examination (mandatory, typed, severity-scored)

R3: Rebuttals

STEP 5: Synthesis (R4, the Chair) and the Committee Verdict

STEP 6: The Pre-Flight Checklist (fail-closed gate)

Execution modes

Mode A: native sub-agent fan-out (the upside)

Mode B: sequential "wear each hat" (the floor; every host can do it)

The degradation ladder

Worked example (abbreviated; all numbers illustrative)

Glossary (define at point of use; here for reference)

Fetch Reference (command, then endpoint)

Agent Tips (shape gotchas worth memorizing)

Fetch safety (required if the host fetches EDGAR/FRED/IR)

Tier Summary

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