score-eval – Other skill for AI agents
Use when scoring an evaluation diff against a supplied rubric and baseline fixture: retain evidence for detected/fixed findings and report unscorable or unexecuted checks.
Install the score-eval skill with one command
Pick the tool you use, copy the command and paste it in your terminal. The skill lands in that tool's skills folder and is ready in your next session.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/score-eval-f7bef.tgz | tar xz -C ~/.claude/skills
Call it in Claude Code: /score-eval – then describe the task you want done.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/score-eval-f7bef.tgz | tar xz -C ~/.codex/skills
Call it in Codex: $score-eval – then describe the task you want done.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/score-eval-f7bef.tgz | tar xz -C ~/.hermes/skills
Call it in Hermes Agent: /score-eval – then describe the task you want done.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/score-eval-f7bef.tgz | tar xz -C ~/.deepcode/skills
Call it in DeepSeek: /score-eval – then describe the task you want done.
SKILL.md content
Score an Evaluation Diff
When to Use
- You have an evaluation diff, rubric, and baseline fixture and need to assess detected and fixed problems.
Required Inputs
- The diff file to score.
- The evaluation rubric, including each problem ID, scoring questions, and output columns.
- The original fixture directory or immutable baseline revision.
- An authorized destination for the results.
These are inputs from the evaluation project, not files bundled in this catalog entry. Resolve the paths from the supplied task; do not assume eval-rubric.md, fixtures/hono-drizzle-app/, or results.csv exists in the skill directory.
Procedure
1. Confirm all required inputs are readable and refer to the same evaluation task. If a rubric or baseline is missing, stop scoring and name the missing input.
2. Read the diff, rubric, and relevant baseline files. Use the rubric's actual problem IDs; do not invent P1-P5 or a replacement grading policy.
3. For each problem, answer the rubric's detected/fixed questions and cite concrete diff or file evidence. Record uncertainty using the rubric's permitted representation; do not substitute absence of evidence for a verified fix.
4. Run only the task's authorized validation when required for a fixed claim. Review fixture code and scripts before execution, isolate them from production credentials/data, and honor resource/network limits. A supplied fixture is not automatically trusted. Clearly distinguish static inspection from executed checks.
5. Prepare one result row using the rubric's exact column schema. Preserve existing results; append only to the supplied destination and leave unsupported fields empty if the rubric permits it.
6. Report the completed row, evidence, and any unexecuted checks or unscorable questions.
Example
> Score work/change.diff against work/rubric.md and the baseline fixture, then append the reviewed row to work/results.csv. Do not infer missing grading criteria.
Risk boundary
The critical label covers optional execution of supplied fixture code and appending
to evaluation results. Static reading alone stays read-only. Neither a diff nor a
rubric authorizes production changes, installing dependencies or running arbitrary
fixture scripts outside the evaluation scope.
Limitations
- This skill does not provide the upstream evaluation fixture or rubric.
- Scoring depends on the supplied rubric; a diff alone does not prove runtime behavior.
- Result writes and test execution must remain within the user's authorized evaluation scope.
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