realtalk
Skill1 starsChanged 3 months agoNo licenceView on GitHub
Post-task reality audit. Runs concrete checks (git status, whether the session's PRs actually merged, files/artifacts left outside the repo, stray branches/worktrees, leftover dev servers/sims/browser sessions) AND forces disclosure of the friction agents normally bury — work that looks done but isn't, workarounds used instead of real fixes, guessed or inferred evidence, deviations from the request, unverified claims — then emits a severity-ranked report with prioritized follow-ups. Use when an agent (or you) just finished a task and you want the real story instead of the victory-lap summary, when you want to verify an "it's merged / tests pass / it's done" claim before trusting it, or to audit a pasted task transcript. Triggers on "/realtalk", "real talk", "what really happened", "audit this run", "what did you actually leave".
In this repository17 other files it gives its agents.
- design-mdSkill
- dieter-rams-designSkill
- disk-cleanupSkill
- e2e-testSkill
- html-reportSkill
- iframelySkill
- im-a-product-designerSkill
- iphone-duo-akSkill
- presentational-componentsSkill
- product-mdSkill
- research-collectorSkill
- simple-copySkill
- simulator-queueSkill
- slack-messageSkill
- steve-jobs-product-designSkill
- task-orchestrator-loopSkill
- test-desiderataSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — 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.