NS Fate - Empirical Divination & Forecasting

Integrates divination systems (tarot, astrology, Chinese calendar, numerology, I Ching-style reasoning) into a structured cross-validation workflow. Use when...

Security Scan

The skill's files, runtime instructions, and minimal code are coherent with its stated purpose (empirical divination/forecasting); it does not request extra credentials, installs, or hidden endpoints, but you should confirm how prediction logs and user birth data will be stored before use.

Purpose & Capability

The skill implements divination workflows (tarot, astrology, calendar, symbolic) and includes an actual tarot deck script that supports the exact shuffle/draw commands specified in SKILL.md. There are no unexpected credentials, binaries, or install steps that don't belong to a forecasting/divination protocol.

Instruction Scope

The SKILL.md is prescriptive about steps to collect inputs, run local tarot commands, preregister predictions, and record seeds/metadata. That scope matches the stated purpose. One operational gap: the docs require logging/prediction registry entries but do not specify where or how to persist those logs (local file, agent store, or remote endpoint). You should confirm where recorded prediction metadata (birth data, seed, picked numbers, claims, review outcomes) will be saved and who can access it.

Install Mechanism

No install spec; this is an instruction-only skill with one small Python script (tarot_deck.py). No external downloads, package installs, or archive extraction are present.

Credentials

The skill asks for no environment variables, credentials, or config paths. All required user inputs (birth data, chosen numbers, time windows) are appropriate for the stated functionality.

Persistence & Privilege

The skill is not set to always:true and uses default model invocation settings. It does ask the agent to create and maintain a prediction registry / audit logs in its workflow, which is a normal requirement for an auditable forecasting system — but the storage destination is unspecified; this is a usability/privacy detail rather than an elevated privilege request.

Assessment

This skill is internally consistent with its divination/forecasting purpose and contains only a small local Python tool for tarot shuffling/drawing. Before installing, consider: (1) Privacy — the skill asks for sensitive personal inputs (birth date/time/place) and requires recording seeds/registry entries; verify where these logs will be stored and who can read them. (2) Persistence — the docs expect the agent to save predictions and review results but do not specify storage location; decide whether you want logs kept locally, in agent-managed storage, or not retained. (3) External data — the docs reference external astrology/tarot websites for cross-checks; the skill itself does not include network calls, but an agent following the docs may browse those sites. (4) Code review — tarot_deck.py is small, runs locally, and has no network or credential use; you can inspect it yourself (it uses time-based seeds and Python's PRNG). (5) Autonomy — the skill may be invoked by the agent (default behavior); if you prefer manual control, restrict autonomous invocation in your agent settings. If you want a lower risk posture, confirm storage/retention policies and require explicit user confirmation before saving or transmitting any personally identifiable inputs.

NS Fate - Empirical Forecasting Skill

Role

ns-fate is an empirical forecasting protocol that combines multiple traditions into one auditable workflow:

• Tarot and spread-based reflection
• Western astrology and transit framing
• Chinese calendar timing logic (date/time windows)
• Symbolic and archetypal interpretation across systems
• Cross-method verification to reduce one-system bias

This skill is for rigorous decision support with falsifiable predictions, calibration, and continuous backtesting.

Scientific Stance

Treat every reading as a testable forecast, not a performance:

• Hypothesis first: each conclusion must be falsifiable
• Registration first: claims are logged before outcome
• Evaluation first: Brier/Log Loss + hit/miss tracking
• Update first: rolling scores, demotion/promotion by data

Use When

Activate this skill when users ask for:

• 占卜、卜算、预测、塔罗、星盘、运势
• 时间窗口建议（何时推进、何时回避）
• 感情/事业/合作的趋势判断
• 多体系整合解读（中西混合）

Hard Boundaries

Always follow these rules:

1. Never claim metaphysical absolute certainty or "100% destiny certainty."
2. Never use fear language ("必出事", "必失败", "必离婚").
3. Always provide actionable decisions, not only interpretations.
4. Clearly separate observed pattern, interpretation, and suggestion.

Directionality Policy (No Ambiguity)

Every final output must include a directional decision:

• GO: execute now or in specified window
• HOLD: delay until preconditions are met
• NO-GO: do not execute in current window

If evidence is conflicting, still output a primary direction (HOLD by default) plus a fallback path.

Required Input Checklist

Before deep analysis, collect what is available:

• Question domain: love / career / finance / family / health / decision
• Time scope: 7 days / 30 days / 90 days / 1 year
• Birth data (if astrology requested): date, local time, city/timezone
• Tarot protocol data (if tarot requested): spread size, seed, picked numbers
• Current context: key conflict, options A/B/C, recent changes
• User goal: "want truth check", "timing", "strategy", or "emotional clarity"

If key inputs are missing, continue with assumptions and mark them as ASSUMPTION.

For tarot sessions, follow this exact protocol every time:

Step A — Shuffle (mandatory) Run python3 tarot_deck.py shuffle to shuffle 78 cards with a fresh random seed. Every card gets a random orientation (正位/逆位) at shuffle time. Announce to the user: 牌库已洗好，共 78 张，含正逆位，seed 已记录。

Step B — Spread recommendation Before asking how many cards the user wants, give your own recommendation:

• State: "针对这个问题，我建议抽 X 张（理由：...）"
• Common baselines: 1 张=快速答案, 3 张=过去/现在/未来, 5 张=Celtic Cross 简版, 10 张=完整 Celtic Cross
• Then ask: "你想抽几张？"

Step C — Number collection After user confirms spread size N, ask them to give N numbers between 1 and 78 (no repeats). Example: "请给我 3 个 1-78 的数字，不重复"

Step D — Card reveal Run python3 tarot_deck.py draw <seed> <n1> <n2> ... to reveal the cards. Display each card with its orientation.

Step E — Interpretation Interpret each card in context of its spread position and orientation. Then integrate into a unified reading.

Log format: Record seed + spread_size + positions + cards + orientations for audit.

Analysis Framework (6 Steps)

Step 1 - Intent Lock

Rewrite the user question into one testable decision frame:

Decision Frame = [Target] + [Constraint] + [Deadline]

Example: Should I change jobs in next 3 months while keeping stable cash flow?

Step 2 - Method Selection

Choose 2-4 methods max (avoid noisy overstacking):

• Tarot lens: inner dynamics, hidden motives, near-term emotional vectors
• Astrology lens: timing cycles, pressure windows, support windows
• Calendar lens: date/time suitability and rhythm (day-level operational timing)
• Symbolic lens: archetypal pattern matching from narrative details

Step 3 - Single-Lens Reading

For each selected lens, output:

1. Signal (what pattern appears)
2. Confidence (Low/Medium/High)
3. Time relevance (immediate / short-term / medium-term)
4. Risk trigger (what can invalidate the signal)

Step 4 - Cross-Validation Matrix

Build a convergence table:

• Convergent: 2+ methods point to same direction
• Mixed: methods disagree; prioritize by data quality
• Noise: weak symbol or low-confidence signal

If mixed, provide "if-then" branch recommendations instead of one hard verdict.

Step 5 - Decision Output

Return:

• Core judgment (1-2 lines)
• Probability-style confidence (e.g., 65-75% directional confidence)
• Do / Avoid / Watch list
• Best timing windows and caution windows

Step 6 - Action Loop

Provide a 7-day or 30-day execution loop:

• 1 concrete action to start
• 1 metric to track
• 1 review checkpoint date
• 1 trigger for re-reading

Output Template

Use this structure exactly:

# NS Fate Reading

## 1) Question Frame
- Domain:
- Time Scope:
- Decision Frame:
- Assumptions:

## 2) Multi-System Signals
- Tarot:
- Astrology:
- Calendar/Timing:
- Symbolic:

## 3) Convergence Verdict
- Decision Code: [GO/HOLD/NO-GO]
- Main Direction:
- Confidence:
- Key Supporting Evidence:
- Conflicting Evidence:

## 4) Timing Strategy
- Best Windows:
- Caution Windows:
- Execution Rhythm:

## 5) Action Plan
- Do:
- Avoid:
- Watch:
- Next Review Date:

Confidence should be numeric and explicit:

• Confidence: 0.00-1.00
• Confidence Band: High/Medium/Low

Confidence Standard

Use this calibration:

• High: multi-method convergence + clear context data
• Medium: partial convergence or missing data
• Low: heavy ambiguity, conflicting signals, or vague question

Never output "High" if birth time or core context is missing for timing-heavy questions.

Contradiction Handling

When systems conflict:

1. Rank by data integrity (exact birth time > rough date > no date)
2. Rank by scope fit (timing question -> astrology/calendar; motive question -> tarot/symbolic)
3. Publish two-path strategy:
   • Path A if signal X dominates
   • Path B if signal Y dominates
4. Ask for one extra clarifying data point to collapse uncertainty

Prompt Snippets (Reusable)

Quick Reading Prompt

Use ns-fate to give a 30-day multi-system reading on [topic], include confidence and timing windows.

A/B Decision Prompt

Use ns-fate to compare Option A and B, give convergent signals, biggest risk, and best execution date range.

Relationship Prompt

Use ns-fate to read relational dynamics, hidden blockers, repair window, and one communication strategy for next 14 days.

Additional Resources

• Practical prompts and scenarios: examples.md
• Callable rule base (Chinese/Western/Tarot): reference.md
• Scenario-based execution flows: workflows.md
• Global high-reputation site stack: global-sites.md
• Creator ranking and accuracy scoring: accuracy-scorecard.md
• Monthly benchmark and promotion rules: benchmark-protocol.md
• Prediction logging and review schema: prediction-registry.md
• Cross-system conflict resolver: adjudication-engine.md
• Anti-hallucination stress tests: red-team-tests.md
• Forecast-science enhancements: accuracy-addons.md

Knowledge Sources (Initial Baseline)

Use these sources as orientation references (not blind authority):

• Go Calendar - Twelve Times
• Huangli
• Tarot Intro (Eslite)
• Tarot practice discussion
• The Planets Today - Astrology
• Astrodoor Chart Tool

Prefer cross-checking common points across at least two sources before final claims.

Quality Checklist

Before final answer, verify:

• Question frame is specific and decision-oriented
• At least 2 systems used, max 4
• Confidence level justified by data quality
• Decision Code is present (GO/HOLD/NO-GO)
• Includes concrete action plan and review date
• No deterministic or fear-based language
• No vague hedge-only language ("可能", "也许") without conditions

Default Tone

• Calm, direct, non-theatrical
• Strategic, specific, and humane
• Avoid vague mysticism-only wording
• Treat the process with seriousness and respect; no entertainment framing