skill-feedback-loop
Skill0 starsChanged 44 days agoLicence not identifiedView on GitHub
The factory's outer loop. Reads where people keep correcting agents (local transcripts, the run ledger, human review comments on merged PRs), finds the skill that owns each repeated failure, and opens one small, evidence-backed PR to improve it for a human to review. Use when the weekly loop runs, when asked to "improve the skills", "run the loop", or "why do agents keep doing X", when a friction report shows a climbing pattern, or when a memory has been used often enough to graduate into a skill.
- Commits and pushes
In this repository21 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/factory-setup/assets/AGENTS.mdAGENTS.md
- agent-memorySkill
- ambition-engineSkill
- code-review-loop-largeSkill
- code-review-loopSkill
- cross-platform-shellSkill
- factory-setupSkill
- issue-triageSkill
- local-code-reviewSkill
- model-routingSkill
- package-releaseSkill
- prose-cleanupSkill
- release-monitoringSkill
- run-ledgerSkill
- service-layerSkill
- skill-authoringSkill
- spec-writingSkill
- test-evidenceSkill
- visual-diffSkill
- worktree-isolationSkill
The file
We split this skill into the rules it gives an agent
10 rules. About 0 are common, 2 are distinctive, and 8 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
8
Very specific
Tied to their project's names, files or tools. Probably skip.
The licence could not be identified — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill 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.
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.