New to Claude Skills? Learn how to install them →

builderio on GitHub

Agent Watchdog

Free

Monitor and audit agent work effectively.

by builderio3.9k stars on builderio/skills
1 views
Updated Aug 4, 2026
Get this skill

Free · Opens the source repo

What Agent Watchdog does

Agent Watchdog is a specialized skill designed for developers and designers who need to oversee the work of AI coding agents like Codex or Claude Code. This skill allows users to watch, audit, and even fix issues in the output of these agents based on a variety of input artifacts such as session IDs, transcripts, pull requests, and logs. By using Agent Watchdog, you can ensure that the work produced by other agents aligns with your original requests and meets the necessary quality standards.

The skill operates in several modes, including watch-only, audit, audit and fix, and compare. Depending on your needs, you can choose to simply monitor an agent's progress, conduct a detailed audit of their output, or even make targeted fixes if you identify clear gaps in their work. The flexibility of these modes makes Agent Watchdog suitable for various scenarios, from real-time monitoring of ongoing tasks to retrospective audits of completed work.

To effectively use Agent Watchdog, you will need to provide it with relevant artifacts that the other agent has worked on. The skill intelligently resolves these artifacts, reconstructs the original user request, and inspects the evidence of what the agent has produced. It categorizes any discrepancies it finds into gaps, bugs, or verification misses, allowing you to understand where the agent's output deviated from expectations. If authorized, it can also make narrow fixes to address identified issues without disrupting unrelated changes.

Overall, Agent Watchdog is an essential tool for anyone who collaborates with AI agents and requires a robust mechanism to ensure quality and accountability in their outputs. It provides a structured approach to monitoring and auditing agent work, making it easier to maintain high standards in software development and design.

When to use it

Use Agent Watchdog when you need to monitor or audit the work of AI coding agents to ensure quality and compliance with your requests.

When not to use it

This skill is not suitable for scenarios where no oversight of AI agents is needed or when broad rewrites are required without clear evidence of gaps.

What you can build with it

Real-time Monitoring

Use Agent Watchdog to monitor an AI agent's progress on a coding task in real-time, ensuring it meets your expectations.

Conducting an Audit

After an AI agent completes a task, utilize Agent Watchdog to audit the output against your original request and identify any gaps.

Fixing Identified Issues

When gaps are found in an AI agent's output, authorize Agent Watchdog to make targeted fixes, improving the overall quality of the work.

How to install Agent Watchdog

View source

1. Install with the skills CLI

npx skills add builderio/skills/agent-watchdog --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by builderio

Agent Watchdog

Watch another agent's work like a reviewer with a pager: wait for completion when needed, reconstruct the request, verify the evidence, and close the gap between what was asked and what actually happened.

Choose The Mode

Infer the mode from the user's wording:

  • Watch only: monitor a session, PR, branch, CI run, or transcript until it reaches a terminal state. Do not edit files.
  • Audit: read the prompt, transcript, diff, tests, CI, comments, screenshots, or final claims and return a gap report. Do not edit files.
  • Audit and fix: audit first, then make narrow fixes for clear gaps. Avoid broad rewrites, branch movement, or speculative changes.
  • Compare: when given multiple sessions or agents, compare their work against the same original request and reconcile the important differences.

If authority is unclear, default to audit-only and say what you would fix.

Resolve The Target

  1. Identify every artifact the user supplied: session ID, transcript path, thread URL, PR, branch, commit, CI run, issue, Slack link, or pasted summary.
  2. Use the host's native thread/history tools, local transcript files, repo logs, GitHub tools, or pasted content to resolve the artifact. Prefer the most direct source over summaries.
  3. If the artifact is still running and the user asked to watch, poll at a reasonable interval until it is done, blocked, stale, or clearly waiting on a human/external system.
  4. If the artifact cannot be resolved, ask for the missing identifier or path.

Reconstruct The Contract

Build a compact contract before judging the work:

  • Original user request and any later changes in scope.
  • Explicit constraints: branch rules, no-edit requests, deadlines, package versions, validation expectations, design requirements, or security/privacy limits.
  • Implied acceptance criteria: user-visible behavior, tests, CI, docs, deploys, screenshots, review replies, or status updates.
  • The other agent's final claims and any "could not do" caveats.

Treat the user's request as the source of truth, not the other agent's summary.

Audit The Evidence

Inspect evidence, not vibes:

  • Read changed files and relevant unchanged files around the touched paths.
  • Check git status/diff without reverting unrelated work.
  • Compare commands the agent claimed to run with actual output when available.
  • Inspect failed or skipped tests, CI logs, browser screenshots, review comments, deploy output, and error traces.
  • For PR/review work, verify unresolved threads and CI state from the source system when tools are available.
  • For UI work, prefer screenshots or browser checks over prose claims.

Classify each issue as:

  • Gap: requested behavior is missing or incomplete.
  • Bug: the implementation likely fails or regresses behavior.
  • Verification miss: the work may be right but the evidence is weak.
  • Scope drift: the agent changed something unrelated or skipped a constraint.
  • No issue: the concern is already handled, with evidence.

Fix Narrowly

When the user authorized repair:

  1. Fix only gaps with clear evidence.
  2. Preserve unrelated local changes and do not move branches unless explicitly asked for that branch operation.
  3. Use existing repo patterns and targeted tests.
  4. Re-run the smallest useful validation after each meaningful fix.
  5. If a fix would require a product decision, credential, destructive action, or broad rewrite, stop and report the decision instead of guessing.

Report

Lead with the outcome. Keep the report short enough to scan:

Status
- Done, blocked, stale, or still running.

Requested
- What the user asked the watched agent to do.

Observed
- What the watched agent changed, claimed, and verified.

Gaps
- Missing behavior, bugs, weak verification, or scope drift.

Fixes made
- Files changed and validation run. Omit this section for audit-only work.

Remaining risk
- Anything still unverified or waiting on CI/review/deploy/human input.

Name exact files, commands, PRs, or thread IDs when they matter.

Frequently asked questions about Agent Watchdog

Similar skills