ai-workflow-framework: Skill for Claude Code

.claude/skills/project-cleanup/SKILL.md

project-cleanup is a skill for Claude Code from satsilem/ai-workflow-framework. It costs 138 tokens per session (2,871 once invoked), scanned A, original, MIT.

An interactive maintenance process for project documentation and reference files. It checks files such as TODO.md, SESSION.md, INSIGHTS.md, CLAUDE.md, and .reference/ for consistency, missing links, and outdated information.

In plain words
What is it for?
Auditing and tidying project notes, checking documentation links, validating reference files, and filling gaps in project instructions.
Why use it?
It finds stale notes, broken file references, missing guidance, and unfinished cleanup work before applying changes. You choose which numbered tasks to run and confirm before changes are made.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: reads .claude/ paths; mentions CLAUDE.md.

This is satsilem/ai-workflow-framework's own configuration. It tells Claude Code how to work on ai-workflow-framework itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-workflow-framework configures →

Reuse

Borrowing it

Nothing to install: this file belongs to satsilem/ai-workflow-framework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/satsilem/ai-workflow-framework/main/.claude/skills/project-cleanup/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/satsilem/ai-workflow-framework

Made for: Claude Code.

Wrote 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.

agentmods badge for project-cleanup

README.md
[![agentmods](https://agentmods.dev/badge/skills/satsilem/ai-workflow-framework/project-cleanup/github.svg)](https://agentmods.dev/skills/satsilem/ai-workflow-framework/project-cleanup)
Your own site
<a href="https://agentmods.dev/skills/satsilem/ai-workflow-framework/project-cleanup"><img src="https://agentmods.dev/badge/skills/satsilem/ai-workflow-framework/project-cleanup/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for project-cleanup

Your own site · 80×15
<a href="https://agentmods.dev/skills/satsilem/ai-workflow-framework/project-cleanup"><img src="https://agentmods.dev/badge/skills/satsilem/ai-workflow-framework/project-cleanup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 138 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,871 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00138 $0.02871
Opus 5.5 $0.00055 $0.01148
Sonnet 5.5 $0.00028 $0.00574
Haiku 4.5 $0.00014 $0.00287

Measured 2mo ago against content hash 0bae874eb20c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

project-cleanup 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 2mo 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.

.claude/skills/project-cleanup/SKILL.md · 317 lines

How it starts

The opening of the file, as written. The whole thing — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Project Cleanup — Enhanced

Complete project maintenance: Validation → Audit → Cleanup → Application.

Each phase presents numbered sub-tasks. User replies with task numbers to run (1,3,5, all, or skip), then those tasks execute sequentially with pauses for confirmation before application.


Preparation — Read all files

Before producing any proposal, read:

  • TODO.md — full file
  • SESSION.md — full file (KEY LEARNINGS + all chronological entries)
  • INSIGHTS.md — full file
  • CLAUDE.md — for gaps and content audit
  • .gitignore — verify local-only working directories are excluded appropriately
  • .reference/INDEX.md — verify it exists and is current
  • .reference/ folder — list all files and check their metadata

Also identify:

  • Project .claude/skills/ directory
  • Global skills directory (if configured for cross-project reuse)

Phase 1 — VALIDATION (Check doc consistency)

Sub-tasks:

1. SESSION.md link audit — Check for broken/outdated file references
2. INSIGHTS.md file validation — Verify referenced files exist
3. .reference/ health check — Verify metadata complete + fresh (Last reviewed ≤ 30 days)
4. CLAUDE.md gap detection — Check if "CLAUDE.md Gaps" from INSIGHTS are documented
5. Broken internal refs in skills — Find stale paths in skill files

→ Which validation tasks to run? Reply: 1, 2, 3, 1,3,5, all, or skip

After user replies:

For each selected task, perform the audit and report findings:

  • Task 1: List broken SESSION.md links + suggested corrections
  • Task 2: List missing files/folders referenced in INSIGHTS.md
  • Task 3: List .reference/ files with missing/stale metadata
  • Task 4: List CLAUDE.md gaps NOT yet documented
  • Task 5: List skill files containing stale .ai-notes/ paths

Present one task result at a time. After all selected tasks complete, ask:

Validation complete. Proceed to Phase 2 (Audit)?
→ Reply: yes, or skip to Phase 3/4

Phase 2 — AUDIT (Check INSIGHTS integrity)

Read the full file on GitHub · 317 lines

Changes

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.

  1. 2mo ago First seen · 317 lines · 138 tokens per session scan A 0bae874eb20c

Subscribe to this mod's changes

project-cleanup is a skill published in the GitHub repository satsilem/ai-workflow-framework (2 stars, last pushed 1mo ago), licensed MIT. It adds 138 tokens to every session and 2,871 once invoked, about $0.0006 per session on Opus 5.5. 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.

Related

project-cleanup compared with skills from other repositories

project-cleanup next to 6 skills from other repositories
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