Borrowing it
Nothing to install: this file belongs to cl-ai-project/cl-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cl-ai-project/cl-mcp/main/.claude/skills/dogfooding-cl-mcp/SKILL.mdgit clone --depth 1 https://github.com/cl-ai-project/cl-mcpWrote 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/skills/cl-ai-project/cl-mcp/dogfooding-cl-mcp)<a href="https://agentmods.dev/skills/cl-ai-project/cl-mcp/dogfooding-cl-mcp"><img src="https://agentmods.dev/badge/skills/cl-ai-project/cl-mcp/dogfooding-cl-mcp/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/skills/cl-ai-project/cl-mcp/dogfooding-cl-mcp"><img src="https://agentmods.dev/badge/skills/cl-ai-project/cl-mcp/dogfooding-cl-mcp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.04425 |
| Opus 5 | $0.00021 | $0.02212 |
| Sonnet 5 | $0.00008 | $0.00885 |
| Haiku 4.5 | $0.00004 | $0.00443 |
Grade A, and why
dogfooding-cl-mcp 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 13d 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 — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dogfooding cl-mcp
Overview
Build a real mid-size Common Lisp project with cl-mcp's own tools, watching for every rough edge along the way. The point is not the project — it is the feedback. Every retry, every confusing error, every tool that surprises you goes into the feedback file.
Core principle: Cheap, disposable projects that exercise the full cl-mcp tool surface produce better feedback than abstract review. Build, notice friction, record it, throw it away.
When to Use
- User asks for dogfooding, feedback collection, or "try cl-mcp on a real project"
- You want to verify a recent cl-mcp change works in practice, not just in unit tests
- You are looking for P1/P2/P3-level improvement candidates to feed into the next PR cycle
Do NOT use for: scaffolding a project the user actually wants to keep, or for unrelated CL work.
Workflow
1. Workspace setup
Scaffold projects live under experiments/ inside the cl-mcp checkout.
This directory is listed in .gitignore, so generated files never appear
in git status and cannot be committed by accident. No project-root
switching is needed.
fs-set-project-root path=. # ensure project root is cl-mcp
fs-get-project-info # confirm
Hydrate deferred tool schemas before any tool call with boolean/integer parameters.
Without this, calls like load-system force=true or inspect-object id=N will fail
with misleading must be boolean/must be integer errors (harness-side issue, not cl-mcp):
ToolSearch select:mcp__cl-mcp__lisp-read-file,mcp__cl-mcp__load-system,mcp__cl-mcp__repl-eval,mcp__cl-mcp__inspect-object,mcp__cl-mcp__lisp-edit-form,mcp__cl-mcp__clgrep-search,mcp__cl-mcp__code-find,mcp__cl-mcp__code-describe,mcp__cl-mcp__code-find-references,mcp__cl-mcp__pool-kill-worker
2. Scaffold with project-scaffold
Call project-scaffold once with destination: "experiments". Save the response — note the absolute_path, the files list, and the framework it echoes back.
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.
- 13d ago First seen · 231 lines · 42 tokens per session scan A 7e1a11ff16dd
dogfooding-cl-mcp is a skill published in the GitHub repository cl-ai-project/cl-mcp (84 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 4,425 once invoked, about $0.0002 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 2026-08-30.
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