# Multi Agent Analysis

> 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.

- Skill: `preetamnath/multi-agent-analysis` (Agent Skill)
- Install (CLI): `npx skillmds@latest add preetamnath/multi-agent-analysis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/preetamnath/multi-agent-analysis/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: preetamnath (https://skillmd.com/u/preetamnath)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/preetamnath/multi-agent-analysis

---


# 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](#output-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
}
```