Delegation Audit

CommunityPopular

hoangsonww

delegation-audit

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.

Overview

Publisher	hoangsonww
Repository	`Claude-Code-Agent-Monitor`
Skill name	`delegation-audit`
Stars	1.1K
Forks	260
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by hoangsonww on GitHub. Read the source before you install it.

Installation

Install the Delegation Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-workflows/skills/delegation-audit
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-workflows/skills/delegation-audit

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor.git /tmp/Claude-Code-Agent-Monitor
mkdir -p .claude/skills
cp -r /tmp/Claude-Code-Agent-Monitor/plugins/ccam-workflows/skills/delegation-audit .claude/skills/delegation-audit

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Delegation Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Delegation Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Delegation Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Markdown tables for the matrix and effectiveness.
Success rates as percentages; durations in human units (e.g. 1m 12s).
Use ▲/▼ when comparing a type's success rate against the session-wide average.
Cite only numbers returned by the API; do not infer success rates that the effectiveness dataset does not provide.
If the dashboard is unreachable, tell the user to start it with npm start from the repo root.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

agents/openai.yaml1 KB

Frequently asked questions

What does the Delegation Audit AI skill do?

Why use Delegation Audit on TypingMind?

Because you install it once and use it with any model. Delegation Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Delegation Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-workflows/skills/delegation-audit. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Delegation Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Delegation Audit?

As many as you like. As long as a model supports skills, you can use Delegation Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Delegation Audit AI skill free?

Yes. It is published on GitHub by hoangsonww under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Delegation Audit

Input

Data Sources

Report Sections

1. Delegation Matrix

2. Effectiveness by Subagent Type

3. Wasted Delegations

4. Rebalancing Suggestions

Output

Bundled files

Frequently asked questions

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