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Audits the DSA problem bank for coverage gaps and proposes new YAML entries.
Passed 16 of 18 test cases with the skill, and 4 of 18 without it.
and 15 more in the full report
14 fixed5 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which configuration file in plugins/gauntlet/data/problems/ contains the target problem counts per category?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies _manifest.yaml as the target count manifest file. | Missed | Passed |
The instructions your model reads when the skill loads.
Survey the DSA problem bank, identify coverage gaps, and propose new YAML entries for human review.
gauntlet:curate)gauntlet:extract)Invoke this skill manually with Skill(gauntlet:gauntlet-curate)
when the problem bank needs a coverage review. The skill is intended
to participate in /update-plugins runs but is not yet wired into
that command (see openpackage.yml registration). It is distinct from
gauntlet:curate, which handles per-annotation knowledge capture
and is what /gauntlet-curate invokes today.
Locate the problem bank at plugins/gauntlet/data/problems/.
Read _manifest.yaml to load the expected NeetCode counts per
category.
Survey current coverage by counting problems in each YAML
file (skipping _manifest.yaml).
Run the analysis script:
cd plugins/gauntlet
python scripts/curate_problems.py data/problems/ --output /tmp/gauntlet-curate-report.md
Identify gaps: categories whose actual count falls below
the neetcode_count in the manifest.
The script sorts gaps largest-first so the worst shortfalls
appear at the top.
test cases passed, vs 4 / 18 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.