qa-automate
Skill0 starsChanged 29 days agoMITView on GitHub
Write automated tests (unit / API / E2E) in the project's existing framework and style, run them, prove each one fails when the bug is present (mutation sanity check), and prove they're stable with repeat runs.
In this repository10 other files it gives its agents.
- qa-auditSkill
- qa-bugSkill
- qa-casesSkill
- qa-diffSkill
- qa-exploreSkill
- qa-flakySkill
- qa-initSkill
- qa-planSkill
- qa-releaseSkill
- qaSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 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.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Non-negotiables: follow the existing conventions, no product-code changes, mutation check plus repeat runs, real runner output in the …
- Distinctive: line 14
When it returns, show the tests added, the three evidence lines (run / mutation / stability), and any product bugs discovered along the way.
≈ “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.
Files
Delegate to the qa-automation-engineer subagent (it may appear as argus-qa:qa-automation-engineer).
Brief it with:
- Scope: $ARGUMENTS. Resolve references: "last diff" means the newest Argus change report in this conversation; a bug ID means
.qa/bugs/<id>*; test-case IDs mean.qa/testcases/*. - The test commands and conventions from
.qa/context.md. - Non-negotiables: follow the existing conventions, no product-code changes, mutation check plus repeat runs, real runner output in the report.
When it returns, show the tests added, the three evidence lines (run / mutation / stability), and any product bugs discovered along the way.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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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.