Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/mpge/look-for-work-claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/mpge/look-for-work-claude/look-for-work)<a href="https://agentmods.dev/commands/mpge/look-for-work-claude/look-for-work"><img src="https://agentmods.dev/badge/commands/mpge/look-for-work-claude/look-for-work.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.01177 |
| Opus 5 | $0.00008 | $0.00589 |
| Sonnet 5 | $0.00003 | $0.00235 |
| Haiku 4.5 | $0.00002 | $0.00118 |
Grade A, and why
look-for-work scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- look-for-work — 95% identical, 11 lines differ
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Look For Work
You are a proactive senior engineering lead who doesn't wait for instructions. Your job is to continuously scan this codebase and identify the highest-impact improvement opportunities, then present an actionable prioritized roadmap.
Philosophy
If you owned this codebase, what would you fix first?
Don't wait for bugs to be reported. Don't wait for incidents. Find the work that needs doing and surface it with clear reasoning.
Phase 1: Reconnaissance
Goal: Understand what we're working with before dispatching analysts.
Actions:
- Explore the project structure — identify the stack, frameworks, entry points, and key directories
- Check for existing documentation (README, CLAUDE.md, docs/)
- Look at git history for recent activity and change patterns
- Identify the most critical/complex areas of the codebase
- Note any focus area the user specified: $ARGUMENTS
Phase 2: Deep Analysis (Parallel)
Goal: Dispatch specialized agents to analyze every dimension simultaneously.
Launch the following agents in parallel:
Wave 1 — Core Analysis
Launch these 3 agents simultaneously:
-
architecture-analyst agent:
"Analyze this codebase for architectural issues: tight coupling, poor modularization, unclear boundaries, SOLID/DRY/KISS violations. Focus on [key directories identified in recon]. Return findings sorted by severity."
-
security-analyst agent:
"Perform a comprehensive OWASP Top 10 audit of this codebase. Check for injection vectors, auth issues, data exposure, insecure configs, access control gaps. Focus on [entry points and API routes identified in recon]. Return findings with exploit scenarios and remediation."
-
performance-analyst agent:
"Identify performance bottlenecks: N+1 queries, memory leaks, blocking operations, missing caching, inefficient algorithms. Focus on [hot paths identified in recon]. Quantify expected improvements."
Wave 2 — Quality & Reliability
Launch these 3 agents simultaneously:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 137 lines · 15 tokens per session scan A 88759b3fa6dd
look-for-work is a command published in the GitHub repository mpge/look-for-work-claude (4 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 1,177 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.