pi-llm-self-verify
AGENTS.md0 starsChanged 3 months agoMITView on GitHub
This repository is a small, dependency-free Pi package. Read README.md before changing behavior. - extensions/self-verify.ts is the Pi entry point. - src/self-verify.ts contains the testable workflow, prompt, tournament, and OpenAI-compatible/Vertex logprob clients. - skills/self-verify/SKILL.md teaches the agent when to call the tool. - Pi loads TypeScript directly; there is no build output to commit. 1. Keep candidate generation read-only: candidate subprocesses may inspect the project but must not write, execute shell commands, commit, or push. 2. Keep the verifier as…
- Installs packages
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,774 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repositoryOne other file it gives its agents.
- self-verifySkill
The file
We split this AGENTS.md into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
Keep candidate generation read-only: candidate subprocesses may inspect the project but must not write, execute shell commands, commit, or …
- Distinctive: line 18
Keep the verifier as a selection aid, never as a test, review, release, or issue-close gate.
- Very specific: line 20
Do not log API keys. Keep provider secrets in environment/Pi auth, not project settings.
- Distinctive: line 21
Keep the public package surface small and avoid new runtime dependencies.
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent instructions
This repository is a small, dependency-free Pi package. Read README.md
before changing behavior.
Shape
extensions/self-verify.tsis the Pi entry point.src/self-verify.tscontains the testable workflow, prompt, tournament, and OpenAI-compatible/Vertex logprob clients.skills/self-verify/SKILL.mdteaches the agent when to call the tool.- Pi loads TypeScript directly; there is no build output to commit.
Workflow
- Keep candidate generation read-only: candidate subprocesses may inspect the project but must not write, execute shell commands, commit, or push.
- Keep the verifier as a selection aid, never as a test, review, release, or issue-close gate.
- Do not log API keys. Keep provider secrets in environment/Pi auth, not project settings. Run
npm run checkbefore handing off a change. - Keep the public package surface small and avoid new runtime dependencies.
- Changes to prompts, scoring, or artifact paths need focused tests and a README update when user-visible behavior changes.
Commands
npm install
npm run check
npm test
npm run typecheckRelease check
package.json is the Pi package manifest. Test a local install with:
pi install /absolute/path/to/pi-llm-self-verifyFor a published/tagged release, use:
pi install git:github.com/andrasat/pi-llm-self-verify@<tag>Release only after npm run check, a clean package dry run, a pushed commit,
and a pushed v0.1.0 tag. npm publish --access public is optional; Pi can
install the tagged Git package directly.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

