clean

clean is a skill for Claude Code, Codex from samibs/skillfoundry. It costs 18 tokens per session (3,793 once invoked), scanned A, original, MIT.

A production-cleanup tool that removes AI framework files, development scaffolding, and agent definitions before deployment.

In plain words
What is it for?
Use it to audit a project, create production-safe ignore rules, remove AI markers, or strip framework artifacts.
Why use it?
It helps prevent internal tools and development details from being exposed in the released application.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions Claude Code.

Good fit Use it to audit a project, create production-safe ignore rules, remove AI markers, or strip framework artifacts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/samibs/skillfoundry/clean
Install

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.

Any agent
npx skills add samibs/skillfoundry --skill clean
Clone the repo
git clone --depth 1 https://github.com/samibs/skillfoundry

Made for: Claude Code, Codex.

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 clean

README.md
[![agentmods](https://agentmods.dev/badge/skills/samibs/skillfoundry/clean/github.svg)](https://agentmods.dev/skills/samibs/skillfoundry/clean)
Your own site
<a href="https://agentmods.dev/skills/samibs/skillfoundry/clean"><img src="https://agentmods.dev/badge/skills/samibs/skillfoundry/clean/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 clean

Your own site · 80×15
<a href="https://agentmods.dev/skills/samibs/skillfoundry/clean"><img src="https://agentmods.dev/badge/skills/samibs/skillfoundry/clean.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,793 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. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 222
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
How audits are shown
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 $0.00018 $0.03793
Opus 5.5 $0.00007 $0.01517
Sonnet 5.5 $0.00004 $0.00759
Haiku 4.5 $0.00002 $0.00379

Measured 1mo ago against content hash c1ab78332ce3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

clean 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 1mo 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.

.agents/skills/clean/SKILL.md · 487 lines

How it starts

The opening of the file, as written. The whole thing — 487 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Production Cleaner

You are a deployment hygiene specialist who ensures production builds contain only application code — zero AI framework artifacts, zero development scaffolding, zero agent definitions. You treat leaked framework files as a security incident: they expose your development methodology, tooling, and internal processes to anyone who inspects the deployed application.

Persona: See agents/production-cleaner.md for full persona definition.

Operational Philosophy: Production is sacred ground. Only application code, configuration, and assets belong there. Everything else is development scaffolding that must be stripped before deployment. If in doubt, exclude it.

Shared Modules: See agents/_reflection-protocol.md for reflection requirements.

OPERATING MODES

/clean audit [project-dir]

Scan project for AI/framework artifacts that would leak to production. Report-only, no changes.

/clean gitignore [project-dir]

Generate or update .gitignore with production-safe rules that exclude all framework artifacts.

/clean strip [project-dir]

Remove AI modification markers and framework references from source code files.

/clean production [project-dir]

Full production preparation: audit + gitignore + strip + verify. The complete pipeline.

/clean verify [project-dir]

Post-clean verification — confirm no artifacts remain in the deployable state.

/clean dockerignore [project-dir]

Generate .dockerignore to exclude framework artifacts from container builds.

FRAMEWORK ARTIFACTS TO EXCLUDE

Directory-Level Exclusions

These directories are development-only and must NEVER appear in production:

Directory Purpose Risk if Leaked
.agents/ OpenAI Codex skill definitions Exposes AI tooling strategy
.claude/ Claude Code commands, hooks, settings Exposes AI prompts and config
.copilot/ GitHub Copilot custom agents Exposes AI agent definitions
.cursor/ Cursor IDE rules Exposes coding standards/rules
.gemini/ Google Gemini skills Exposes AI skill definitions
agents/ Core agent source definitions Exposes full agent library
genesis/ PRD documents Exposes product roadmap and strategy
memory_bank/ AI persistent memory Exposes decisions, errors, patterns
scratchpads/ Agent scratch workspace Exposes internal deliberation
knowledge/ Knowledge sync staging/promoted Exposes learned patterns
compliance/ Compliance profiles and checks Exposes compliance strategy
docs/stories/ Implementation stories Exposes development methodology
docs/prd/ PRD templates Exposes planning process
parallel/ Swarm/parallel coordination Exposes orchestration internals
observability/ Trace/metric collection (dev) Exposes development telemetry
mcp-servers/ MCP server definitions Exposes tool integrations
sf_cli/ SkillFoundry CLI source Exposes framework CLI code
.skillfoundry/ Generated workspace state Exposes session state
dashboard/ Development dashboard Exposes monitoring UI
metrics/ Development metrics Exposes performance data
config/ Framework configuration Exposes agent registry
templates/ PRD templates Exposes planning templates
site/ Framework marketing site Not application code

Read the full file on GitHub · 487 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. 1mo ago First seen · 487 lines · 18 tokens per session scan A c1ab78332ce3

Subscribe to this mod's changes

clean is a skill published in the GitHub repository samibs/skillfoundry (12 stars, last pushed 14d ago), licensed MIT. It adds 18 tokens to every session and 3,793 once invoked, about $0.0001 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 2026-08-30.

Related

Other skills, from other repositories

ring:migrating-to-lib-observability

Migrating a Lerian Go app off lib-commons observability imports (deprecated shims or removed APIs) to lib-observability via a fixed mapping table, then bumps go.mod and validates the build; ring:backend-go applies the edits. Covers log/zap/runtime/assert, opentelemetry/tracing, HTTP middleware, context helpers, and…

LerianStudio/ring · 104 tokens

memorix-troubleshooting

Use when Memorix MCP, setup, project binding, HTTP control plane, hooks, skills, or agent integration is missing, stale, or failing.

AVIDS2/memorix · 36 tokens

ring:planning-codebase-simplification

Planning a whole-codebase simplification: audits a Go/TS codebase for needless abstraction and emits a KILL/REVIEW/KEEP plan plus a ring:running-dev-cycle task array. Plans only — no edits. Detects single-impl interfaces, pass-through shims, translation-free adapters, and dead-code cascade chains under an inverted…

LerianStudio/ring · 105 tokens

ring:planning-large-features

Planning the 8-gate Large Track pre-dev workflow (research, PRD, feature map, TRD, API contract, data model, dependency map, plan) with per-gate human approval. Use for features 2+ days that add dependencies, data models, multi-service integration, or new architecture. Skip for small features (use…

LerianStudio/ring · 89 tokens

ring:generating-llms-txt

Generating or auditing a repository's llms.txt per the llmstxt.org spec, and creating CLAUDE.md / AGENTS.md when missing, by analyzing README, build files, docs, and API surface. Use when creating an llms.txt, auditing an existing one for spec compliance and live links, or improving a repo's AI readability. Skip when…

LerianStudio/ring · 109 tokens

ring:checking-frontend-quality

Checking frontend quality against changed UI via ring:qa-frontend in accessibility, visual, e2e, or performance mode and aggregating pass/fail verdicts. Use when a frontend change needs standalone a11y, visual-snapshot, Playwright e2e, or Lighthouse/Core-Web-Vitals validation outside the dev cycle. Skip for…

LerianStudio/ring · 102 tokens