test-and-verify
Skill6 starsChanged 40 days agoMITView on GitHub
Use after implementing code to systematically verify behavior, tests, regressions, and important edge cases.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- melconcoast/code-ideatheir own version, first seen Nov 2, 2026
- sainzs/santiagosainz-skillstheir own version, first seen Oct 13, 2026
- lucasrafaldini/paperdecktheir own version, first seen Sep 30, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- melconcoast/code-idea★ 4same name
- lucasrafaldini/paperdeck★ 1same name
- sainzs/santiagosainz-skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository36 other files it gives its agents.
- bioinformatics-planningSkill
- biology-literature-analysisSkill
- biology-paper-analysisSkill
- chemistry-research-analysisSkill
- skill-authorSkill
- codebase-explorerSkill
- codebase-understandingSkill
- code-reviewSkill
- debug-systematicallySkill
- implementation-plannerSkill
- implementation-reviewSkill
- ledger-tasks-yyloSkill
- algorithm-learningSkill
- system-design-basicsSkill
- defensive-security-reviewSkill
- threat-modelingSkill
- data-analysisSkill
- tutorSkill
- experiment-analysisSkill
- model-evaluationSkill
- numerical-methodsSkill
- mathematics-problem-solverSkill
- proof-solvingSkill
- physics-research-analysisSkill
- data-cleaningSkill
- data-visualizationSkill
- evidence-checkerSkill
- evidence-comparisonSkill
- experimental-planningSkill
- literature-synthesizerSkill
- reproducibility-auditSkill
- research-questionSkill
- source-verificationSkill
- api-designSkill
- frontend-planningSkill
- technical-editorSkill
The file
We split this skill into the rules it gives an agent
6 rules. 0 are common, 6 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
6
Distinctive
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 10
Verify a completed coding change instead of assuming that a successful edit means the task is complete.
- Distinctive: line 17
Add focused tests when coverage is missing and the task warrants them.
- Distinctive: line 18
Run the narrowest useful test first.
- Distinctive: line 19
Run broader checks when appropriate.
- Distinctive: line 21
Check formatting, linting, types, and build status when relevant.
- Distinctive: line 23
Never claim a test passed unless it actually ran successfully.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Test and Verify
Goal
Verify a completed coding change instead of assuming that a successful edit means the task is complete.
Workflow
- Inspect the diff.
- Identify the behavior changed.
- Find existing tests that cover it.
- Add focused tests when coverage is missing and the task warrants them.
- Run the narrowest useful test first.
- Run broader checks when appropriate.
- Inspect failures rather than hiding or weakening tests.
- Check formatting, linting, types, and build status when relevant.
- Report exactly what was run and what was not run.
- Never claim a test passed unless it actually ran successfully.
Final report
- Changed behavior
- Tests/checks executed
- Results
- Remaining risks
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.

