# Delegation Audit

Audit model delegation and subagent effectiveness for a session, which models handled...

- Repository: https://github.com/hoangsonww/Claude-Code-Agent-Monitor (1136 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-10-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill delegation-audit -g -a claude-code -y`
Codex: `npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill delegation-audit -g -a codex -y`
Cursor: `npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill delegation-audit -g -a cursor -y`
Gemini CLI: `npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill delegation-audit -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add hoangsonww/Claude-Code-Agent-Monitor`

## Description

Audit model delegation and subagent effectiveness for a session, which models handled which subagent types, per-type success rates and average durations, and wasted delegations (heavy models on trivial work or types that consistently fail), using the Agent Monitor workflow intelligence API. Use when reviewing how a session delegated work across models and subagents.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Delegation Audit

Audit how a Claude Code session delegated work: model-to-subagent mapping and whether each delegation paid off.

## Input

The user provides: **$ARGUMENTS**

A session ID. If empty, fetch `GET /api/sessions?limit=1` and audit the most recent session, stating which one.

## Data Sources

| Endpoint | Returns |
|----------|---------|
| `GET /api/workflows/{sessionId}` | The `modelDelegation` dataset (which models are delegated which subagent types) and the `effectiveness` dataset (per-type completion/success rate, avg duration, task success) |
| `GET /api/agents` | Raw subagent records (`type`, `model`, `status`, `depth`, `parent`) to corroborate counts and statuses |

## Report Sections

### 1. Delegation Matrix
From `modelDelegation`: a model × subagent-type table of how many agents of each type each model ran.
| Model | explore | code-review | debugger | ... | Total |
|-------|---------|-------------|----------|-----|-------|

### 2. Effectiveness by Subagent Type
From `effectiveness`: per type, the success rate and average duration.
| Subagent type | Count | Success rate | Avg duration | Verdict |
|---------------|-------|--------------|--------------|---------|
Mark types below ~70% success as low-yield.

### 3. Wasted Delegations
Flag, with evidence:
- A heavy model (e.g. Opus) assigned to a simple/low-stakes subagent type that a cheaper model handled successfully elsewhere, candidate for rebalancing.
- Subagent types with low success rates (effort spent, task not completed).
- Duplicate delegations: the same type spawned repeatedly with poor success (retry churn).

### 4. Rebalancing Suggestions
Concrete model reassignments grounded in the matrix and effectiveness data. State the type, the model used, the success rate, and the suggested model, only where the data supports it.

## Output

The rest: https://github.com/hoangsonww/Claude-Code-Agent-Monitor/blob/HEAD/plugins/ccam-workflows/skills/delegation-audit/SKILL.md