Multi Agent Analysis

Multi-Agent Analysis

When to use

You want subagents to do the legwork on a question and hand you a grounded answer to judge.

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 (parallel)

Pick N by breadth, then dispatch all in one message so they run concurrently:

• Size: 1 for a focused question, 2–3 when it splits into independent angles or surfaces. Cap at 3.
• Dispatch: one message, multiple Agent calls. Model per task — opus for architectural/design judgment, sonnet for mapping, code-tracing, or doc/web research.
• Brief each: the problem statement, its own angle, and file paths (not pasted contents). Ground every claim in source it read; return the [Findings schema](#output-schema), not a raw dump. Also have it flag anything material it notices outside the question.

Step 3 — Ground and apply your verdict

Collapse duplicates first — the same finding from 2+ subagents is one, keep its highest confidence. Then sort by confidence into bands and judge:

• keep (≥ 0.80): re-check each against source yourself — read the cited code/doc; don't act on an unverified summary.
• triage (0.70–0.80): contested — if it's decision-driving, get an independent check first (invoke the triage skill, or read the source yourself).
• drop (< 0.70): list it, don't act.

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 — the user decides what to apply.

Rules

• Read-only. Analyze and recommend; leave edits and execution to the user or a build skill.
• Recursion guard. Subagents must not fan out their own subagents — keep to one level.

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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
}

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: preetamnath
• Source: preetamnath/agent-skills
• License: MIT
• Homepage: https://www.preetamnath.com/blog/agent-skills

Install and usage instructions live in the source repository linked above.