model-pyramid

Right-size MODEL + EFFORT for the session and for each subagent at fan-out time, and decide whether to attach an advisor. Two axes: capability gap → change model; thoroughness gap → change effort. Use when spawning / fanning out / delegating subagents, or when asked which model or effort something should get: "$model-pyramid". NOT API price shopping.

Pick model and effort for the session and for every subagent you spawn, then say so in one line each. This skill recommends and reports — it never spawns agents, edits configs, or blocks you.

Everything numeric here is dated (stamp: metadata.model_baseline). Any point version (e.g. 5.1, 5.5) or a silent weight swap under the same name ⇒ re-verify defaults, thinking, pairing and what it touched; a new model generation ⇒ full re-sweep, your evals included.

The two axes (use these, not a rule table)

• Claude had the context, tried — at higher effort too — and still got it wrong → capability gap → change the MODEL.
• Claude got it wrong by skipping a file, not running tests, not double-checking → thoroughness gap → change the EFFORT.

Effort is the main thinking-depth control — and more: it governs all response tokens (text, tool calls, thinking) — how many files get read, how much gets verified, how far a task runs before checking in. Lower effort ⇒ fewer tool calls.

⛔ The corollary that kills the most common mistake: search / exploration / repeated tool calling is the last place to economise on effort. Cutting effort on a search agent buys an agent that stops looking. Hold it or raise it (not to xhigh by reflex — see below).

Defaults: start here, move on evidence

1. Model — subagents inherit the session model; that is the correct default. Override only for a reason you can name.
2. Effort — set it explicitly. Omitted on the API = that model's default: Opus 5.5 medium; Fable 5.1, Opus 5, Sonnet 5 high; Haiku 4.5 none. A bare Agent-tool call inherits the session's (references/runtime-knobs.md).
3. Adjust with evals, not vibes. Step down where quality holds, up where it doesn't. Carrying settings over from an earlier model generation ⇒ re-sweep, don't reuse.

Sizing a fan-out

Classify per task, never per batch. One spawn of five mixed tasks gets five decisions.

Task shape	Model	Effort	Why
Peer co-work — equal-difficulty shards, judge panels, adversarial verifiers, one delegated deep task	inherit	inherit	It is the same work, split. Cutting either knob cuts the work. An independence verifier (blind judge, fresh red team) is non-fork — a fork (Claude Code default) shares its author's context.
Search / exploration — codebase sweep, web research, evidence gathering	inherit	inherit or raise	Effort governs tool-call volume. This is the axis you raise for search.
High-volume homogeneous lookups (~20+ cheap, near-identical)	inherit — or drop one tier (Opus→Sonnet)	one step down — or inherit if the tier dropped	One knob, not both (clamp); effort is usually the safer one.
Long-horizon autonomous run (>30 min, token budgets in the millions)	Opus 5.5; Fable 5.1 when the gap is capability	xhigh	xhigh is defined for exactly this.
Anything else	inherit	the model's default, written out	No reason to move a knob ⇒ don't move it — but name the level.

Clamps

• At most one knob per layer — one tier down or one effort step, not both.
• Two layers is the norm. A third layer, or a bottom-tier pick from a frontier session, needs a one-line justification in the report.
• No hard floor. low is a documented, legitimate subagent setting — justify it, don't ban it.
• An explicit user override wins verbatim. Advisory means advisory.

Before you emit xhigh or max

• Raise max_tokens — 64k is the documented start, 128k for long agentic turns (Opus 5.5 thinks more per turn; Fable 5.1 wants it large from high up). It caps thinking plus text.
• Check the level exists on that model — an unsupported level silently falls back to the highest supported level at or below it.
• Thinking is always on for Opus 5.5 / Fable 5.1 / Fable 5 — thinking:disabled or budget_tokens ⇒ 400 at any effort; lower effort instead. (Opus 5: 400 only at xhigh/max.)
• max is for genuinely frontier problems — elsewhere it adds cost for small gains. On Opus 5.5, reserve xhigh/max for a measured quality gain.

Cost levers that are not "pick a cheaper model"

• Advisor — a stronger model consulted only at decision points. Fits long multi-step tasks where most turns are routine but plan quality decides the outcome; adds little on short tasks. Legal for every model it attaches to; no pairing row (Opus 5.5 today) ⇒ no advisor until a test request with that pair succeeds. → references/orchestration.md
• opusplan — Opus in plan mode, Sonnet for execution: free when the task genuinely splits that way.
• Effort down-step — usually a bigger, safer lever than a model down-step: it degrades gracefully and applies per request.

The cache trap

Changing model or top-level effort invalidates the prompt cache. Hold one level per cached conversation — vary effort across workloads, or use per-message effort (beta), which keeps the cache on Opus 5.5 / Fable 5.1 / Opus 5.

Report

One line per agent:

text

<label>  model=<alias|id>  effort=<level>  rule=<peer|search|bulk|long-horizon|default|override>  [flags]

Flags worth emitting: inherited, justified:<reason>, override, max_tokens-raised, cache-hold, advisor:<model>, non-fork, degraded:<what the runtime could not express> (effort-not-expressible only if neither Workflow opts.effort nor agent-type effort: frontmatter is available). Each line carries its rule + flags, so it survives compaction.

Files

File	Load when
references/model-and-effort.md	a non-session model is named, or you need a model's default, levels or thinking legality
references/orchestration.md	an advisor, opusplan, verifier/judge fan-out or >30-min run is on the table
references/runtime-knobs.md	emitting knobs for a concrete runtime (Claude Code, Agent tool, Workflow, agent frontmatter, API, Codex)
scripts/check_plan.mjs	a plan JSON exists — run it, don't read it

Mechanical check

bash

node scripts/check_plan.mjs '{"agents":[{"label":"reviewer","model":"claude-opus-5-5","effort":"max"}]}'

Checks only table facts (levels, max_tokens, thinking, advisor pairing, cache, search/both-knobs cuts vs the session's resolved effort). Unknown models are reported (model-unknown: re-verify this skill), never passed; aliases get no model-specific verdict. Zero findings = nothing fired, not "verified"; whether your sizing is wise is not judged.