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preetamnathpreetamnath/agent-skills/skills/multi-agent-analysis/SKILL.md

multi-agent-analysis

Skill4 starsChanged 7 months agoMITView on GitHub

Dispatch 1–3 subagents to analyze or verify something, then judge their findings yourself. TRIGGER when: user asks for 'multi-agent analysis', 'use subagents to analyze/verify', or 'use parallel subagents' to investigate something.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Task list: if the ask has independent parts, list them first (TaskCreate) so none is dropped.

    line 13
  2. Distinctive:

    Size: Use 1 subagent by default for a focused question or when scope and complexity are limited.

    line 17
  3. Distinctive:

    Add a tree / ASCII map or table where it aids understanding — current vs proposed, file map, or flow.

    line 44

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Multi-Agent Analysis

Steps

Step 1 — Frame the problem

  • Frame: restate the problem in a line or two and name its type — verify a claim/fix · which answer is correct · architecturally correct + simplest · how something works.
  • Task list: if the ask has independent parts, list them first (TaskCreate) so none is dropped.

Step 2 — Size and dispatch

  • Size: Use 1 subagent by default for a focused question or when scope and complexity are limited. Use 2–3 subagents only when the problem's scope, size, or complexity is large enough to create independent angles worth analyzing in parallel.
  • Dispatch: send all selected Agent calls in one message. Model per task — opus for architectural/design judgment, sonnet for mapping, code-tracing, or doc/web research.
  • Brief each:
    • What to pass: the problem statement, its own angle, and file paths (not pasted contents).
    • Ground every claim in source it read.
    • Return the Findings schema, not a raw dump.
    • Flag anything material it notices outside the question.
    • Don't fan out — no subagents of its own; keep the tree one level deep.

Step 3 — Ground and apply your verdict

Collapse duplicates first — the same finding from 2+ subagents is one, keep its highest confidence. Then judge every finding at c ≥ 0.70 yourself: read the cited code or doc, and don't act on a summary you haven't verified. List anything below 0.70 without acting on it.

Then apply your own verdict on top: agree, correct, or overrule each with reasoning — never relay verbatim. Where findings conflict, resolve deliberately against source; don't average.

Step 4 — Present for decision

Lead with the answer, then report in this shape:

**Analysis result:**
- Answer: [one-line plain-language answer]
- Findings: [claim — your verdict (agree / correct / overrule) — confidence 0.00–1.00, one per line]
- Observations: [material finding outside scope | none]
- Open questions: [unresolved item | none]

Add a tree / ASCII map or table where it aids understanding — current vs proposed, file map, or flow. Stop there — analyze and recommend only; the user or a build skill decides what to apply.


Output Schema

Findings {
  problem: string,                 // the framed problem statement
  findings: [ {
    claim: string,                 // discovery or recommended action, one line
    reasoning: string,             // why — or pro/con — as appropriate
    evidence: string,              // file:line, or doc/URL it's grounded in
    confidence: number             // 0.00–1.00
  } ],
  observations: string[],          // material findings outside the framed question
  open_questions: string[]         // what could not be resolved from source
}

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