Individual skill
con-artist
Audit whether tests detect broken behavior by tracing assertions and running narrow controlled mutations in an isolated workspace; use for test-quality reviews, not routine test execution.
skills/con-artist/SKILL.md
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SKILL.mdcore · 5,781 bytesSKILL.mdcore · 5,781 bytesagents/openai.yamlasset · 205 bytesassets/unittest_startup.pyruns · 2,073 bytesreferences/existing-tests.mddoc · 6,431 bytesreferences/native-unittest-batch.mddoc · 7,279 bytesreferences/python-audit-advanced.mddoc · 9,006 bytesreferences/python-audit-batch.mddoc · 5,089 bytesreferences/python-audit-probes.mddoc · 5,792 bytesreferences/python-audit.mddoc · 9,093 bytesreferences/python-context.mddoc · 8,970 bytesscripts/audit.pyruns · 39,112 bytesscripts/context.pyruns · 17,555 bytes
Read excerpt
# Con Artist
> Your mock is very impressed with itself.
## Check what the test actually buys
Trace the requested assertions far enough to establish the actual exercised effect
and select a reachable fault. Follow unresolved bindings, mocks and relevant setup;
reading every intermediate wrapper is not itself evidence. Reuse known instructions,
runner and source context. Keep discovery inside the permitted project root; a
broad suite need not become a reading list of unrelated tests.
Use the evidenced runner and configuration; reuse a valid correct-code baseline.
Choose one meaningful fault at the requested boundary, such as acknowledging