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/samibs/skillfoundryWrote 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/samibs/skillfoundry/clean)<a href="https://agentmods.dev/commands/samibs/skillfoundry/clean"><img src="https://agentmods.dev/badge/commands/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.
<a href="https://agentmods.dev/commands/samibs/skillfoundry/clean"><img src="https://agentmods.dev/badge/commands/samibs/skillfoundry/clean.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.03766 |
| Opus 5.5 | $0.00000 | $0.01506 |
| Sonnet 5.5 | $0.00000 | $0.00753 |
| Haiku 4.5 | $0.00000 | $0.00377 |
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.
How it starts
The opening of the file, as written. The whole thing — 481 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 |
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.
- 1mo ago First seen · 481 lines · 0 tokens per session scan A bf34a653a791
clean is a command published in the GitHub repository samibs/skillfoundry (12 stars, last pushed 17d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,766 tokens. 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 2026-09-03.
Other commands, from other repositories
act
Execute the implementation plan with TDD.
tailtest
Generate or update tests for $ARGUMENTS.
sessions
Generate implementation session prompts from a PRD or research doc.
deploy
Command "deploy" from PraveenJayaprakash-JP/repomemory, covering deployment workflow, 1. pre-deploy checks, 2. build verification, 3. environment validation and 4. deployment steps (platform detection).
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.