Individual skill
acceptance-checks
Turns the acceptance criteria a task states into executable checks and runs them against the finished outputs before delivering, rather than trusting that a correct-looking analysis satisfies them; rehearses the hidden condition when the grader scores unseen instances from a described family; treats a stated formula, update rule or predicate as the oracle to implement first; so that every stated path, schema, unit, rounding rule, ordering, tolerance, threshold, named method and version, prescribed heading and self-consistency formula becomes a small test, any checker the task ships is run as the exit criterion, derived quantities are recomputed from the primitives, and conventions such as units, signs, coordinate frames and code tables are transcribed into named functions with hand-checked cases. Use whenever a task states how the result will be judged mechanically, ships a validation script, or specifies output formats and tolerances; a report a reader grades needs only its headings and files checked once, and free-form exploration with no stated criteria does not need it.
backend/cli/skills/core/acceptance-checks/SKILL.md
Source commit a08e0ad0ad3d6448123039ee4659163eb2e35d99
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Network or broad shell
- Last checked
- Nov 2, 2026
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Repository context
- Repository stars (not skill ratings)
- 4,352
- Repository last updated
- Nov 6, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
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SKILL.mdcore · 18,461 bytes
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# Acceptance checks
Most specified work is judged mechanically: a script opens your files, reads named
columns, compares numbers to tolerances and stops at the first violation. When a task
tells you how it will be judged, it has handed you the test suite. Write it down, run it,
and only then deliver.
The failure this prevents is not sloppiness. It is a correct analysis delivered with a
column named `sample` where the specification said `sample_id`, an angle in degrees where
radians were required, or a fraction that sums to 0.999 where exactly one was expected.
When the output is a report a person or a model will read and grade (a trace, a
write-up with prescribed headings), there is no mechanical judge to anticipate. The
whole check is that the prescribed headings and files exist and that the numbers in