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advisor-orchestrator-worker

Use when a task is too large for one model pass, needs parallel research or generation across many subtasks (like researching a dozen competitors at once), or the user asks to orchestrate multiple models, split work across a model team, run an advisor-worker loop, have a stronger model review the plan while cheap workers execute, or says "too big for one model" or "fan this out". Not for single-file edits or tasks one model handles in one pass.

75

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Medium

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured orchestration skill: a clear validated multi-step loop, executable bash with safe fallbacks, and clean one-level reference splits. Minor tightening of the budget/degraded-mode prose and de-templating the inline snippet would push it higher.

Suggestions

Tighten the budget paragraph and degraded-mode explanation to their operative rules; the supporting rationale can be trimmed without losing the guidance.

Make the inline worker-dispatch snippet fully self-contained (show the pids=()/wait loop and variable setup) or move the full version into a reference and keep only the canonical form inline.

Consider extracting the per-wave batching and reaping discipline (batches of 3, per-pid wait, dispatch-order reads) into worker-brief.md so the body stays a lean overview of the loop.

DimensionReasoningScore

Conciseness

Dense and lean with no concept-fluff Claude already knows, but a few rationale-heavy passages (the budget-shape paragraph, the degraded-mode explanation) could be tightened without losing guidance.

4 / 5

Actionability

Provides concrete executable bash (worker dispatch, advisor consult via perl alarm) and complete fallback code in references, but the inline dispatch snippet relies on template placeholders ($brief, $out, pids+=()) that need surrounding setup.

4 / 5

Workflow Clarity

The 7-step loop (Frame→Plan→Plan review→Delegate→Verify→Synthesize→Taste pass) has an explicit Verify checkpoint ('run the actual command, read the actual output'), a FIX→redispatch feedback loop, escalation boundaries, and a status board — full validation for this batch/parallel operation.

5 / 5

Progressive Disclosure

Core loop and hot-path dispatch live inline while the heavier formats/fallbacks are split into three one-level-deep references (advisor-consult.md, worker-brief.md, fallbacks.md), each referenced by exact path in the body with no nested references.

5 / 5

Total

18

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, third-person description that concretely states what the skill does, gives natural trigger phrases with synonyms, and carves out a distinct niche with an explicit negative boundary.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — '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' — with comprehensive coverage of the orchestration scenarios.

5 / 5

Completeness

Explicitly answers both 'what' (orchestrate a multi-model team, parallel research/generation, advisor-worker loop) and 'when' ('Use when a task is too large for one model pass...'), plus a concrete negative boundary ('Not for single-file edits or tasks one model handles in one pass').

5 / 5

Trigger Term Quality

Includes natural user phrases a person would actually say, with synonyms: 'too big for one model', 'fan this out', 'split work across a model team', 'orchestrate multiple models'.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (multi-model orchestration) and includes an explicit out-of-scope clause ('Not for single-file edits or tasks one model handles in one pass'), minimizing conflict with single-pass skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
Shubhamsaboo/awesome-llm-apps
Reviewed

Table of Contents

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