stabilize
Skill87 starsChanged 9 days agoLicence not identifiedView on GitHub
USE ONLY WHEN A HUMAN EXPLICITLY INVOKES IT — never auto-select or run this proactively: not after adding a feature, fixing a bug, or finishing a task, not as a routine or ambient health check, and not as a step inside another workflow. This is a deliberate, expensive workflow. Once a human explicitly starts it with /stabilize (Claude Code) or $stabilize (Codex) — typically the night before a release, or as a one-off whole-tree validation — it drives Daintree to a fully green, stable state across every check we can run: typecheck/lint/format, unit, integration, knip (local only), build, smoke, and the full Playwright E2E surface (core, all seven full-* buckets, and the nightly memory-leak soak). Local-first and strictly serial by OS — the local Mac (macOS) to green first, then the cross-platform stabilize.yml GitHub workflow one OS at a time, Linux to green then Windows to green — fixing real failures in batches and re-validating each fix with the narrowest run that proves it, plus release dry-runs when releasing. The budget is ONE full stabilize.yml run per OS; everything after it is a scoped re-run. Never run Linux and Windows in parallel; a bug caught on Linux that also breaks Windows would waste an expensive Windows run.
- Deletes or force-pushes
- Commits and pushes
In this repository8 other files it gives its agents.
- AGENTS.mdAGENTS.md
- assistant/AGENTS.mdAGENTS.md
- assistant/CLAUDE.mdCLAUDE.md
- CLAUDE.mdCLAUDE.md
- optimizeSkill
- demo-video-creatorSkill
- release-packagesSkill
- releaseSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
27 rules. About 0 are common, 13 are distinctive, and 14 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈13
Distinctive · estimate
This author's own choices. Worth a look.
14
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.