Conciseness

The body is lean and assumes competence throughout — every sentence carries non-obvious operational detail (batch waves of 3 for quota, per-pid wait because a collective wait reports only the last status, perl alarm because timeout(1) is missing on stock macOS, ~100 KB brief cap). Not a 5 because time-sensitive version pins ('default: Gemini 3.8 Flash', 'current July 2026') appear inline rather than in a deprecated/old-patterns section, which the rubric flags as a conciseness penalty even though the 'models are knobs' framing partially mitigates it.

Actionability

Fully executable, copy-paste-ready guidance: the worker dispatch is a complete bash snippet (mktemp, env -i, subshell, pid reaping) and the advisor consult is an exact command line with a portable timeout. Specific failure paths (non-zero exit or empty $out → retry via API fallback → no key: ESCALATE) and a concrete status-board format make the common cases fully covered.

Workflow Clarity

The 7-step loop is clearly sequenced with explicit validation checkpoints: tool checks at frame time, two mandatory advisor consults, a verify step with per-result PASS/FIX/ESCALATE verdicts, redispatch on failure ('never hand-patch a substantive failure; redispatch instead'), explicit escalation boundaries, a stated budget rule, and defined stop conditions. This matches the 'clear sequence with explicit validation steps; feedback loops' anchor exactly.

Progressive Disclosure

SKILL.md is a well-organized overview holding the hot path, with three clearly-signaled one-level-deep references (references/worker-brief.md, references/advisor-consult.md, references/fallbacks.md), all of which exist and none of which nest further. The split is appropriate: formats and fallback commands live in the reference files, orchestration logic inline, matching the 'clear overview with well-signaled one-level-deep references' anchor.

Specificity

Concrete actions are named — 'needs parallel research or generation across many subtasks', 'orchestrate multiple models', 'run an advisor-worker loop', 'have a stronger model review the plan while cheap workers execute' — which matches the 'lists several specific actions; minor gaps' anchor. It falls short of 5 because the actions appear only inside trigger clauses rather than as a comprehensive statement of what the skill does (no mention of the plan/verify/synthesize loop or deliverables).

Completeness

The 'when' is explicit and excellent ('Use when a task is too large for one model pass... or says "too big for one model" or "fan this out"'), and the 'what' is recoverable from the listed actions (parallel research/generation, plan review by a stronger model while cheap workers execute). It sits between the 3 anchor (clear what, weak when — the inverse situation) and the 5 anchor, because the what is never stated as an explicit capability sentence.

Trigger Term Quality

Strong natural-phrase coverage including verbatim user phrasings — "too big for one model", "fan this out", 'split work across a model team', 'orchestrate multiple models' — matching the 'good keyword coverage; a few natural terms missing' anchor. It is not a 5 because common synonyms like 'multi-agent', 'parallelize', 'delegate', or 'swarm' are absent.

Distinctiveness Conflict Risk

A clear niche (multi-model orchestration with an advisor-worker loop) with distinct triggers and an explicit negative boundary — 'Not for single-file edits or tasks one model handles in one pass' — giving minimal conflict risk with other skills. The quoted trigger phrases ('fan this out', 'too big for one model') are unlikely to fire for a wrong skill.