Content
56%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is well-organized with concrete commands, a clear two-path workflow (file vs. pasted text), and proper use of one-level-deep references. Its real defects are executable-correctness and redundancy: the documented scores.json key format does not match the bundled calculator's expected keys, a referenced requirements.txt is missing from the bundle, and the dimension list/commands are repeated across sections that duplicate the reference file.
Suggestions
Fix the scores.json example to use the exact keys scripts/calculate_scores.py expects ("Problem Formulation", "Methodology", ...) — or normalize keys in the script — so the documented example works verbatim.
Remove the broken requirements.txt pointer (the file is absent) and instead inline the pinned dependencies or add the file to the bundle.
State the 8-dimension list and 1–5 scale once, deferring both to references/evaluation_framework.md, and show the extraction command once; add a checkpoint to verify extraction output and check the calculator's warnings for missing dimensions.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly lean and does not explain known concepts, but includes noticeable redundancy that could be tightened: the 8-dimension list appears in 'Key Features', again in full under 'Implementation Details', and again in references/evaluation_framework.md; the extraction command is shown three times; and the 1–5 scale plus 'The extraction script is designed to locate the file even if the full path is not provided' restate content that belongs in the reference file. This matches anchor 3 ('mostly efficient but includes some unnecessary explanation or could be tightened') rather than anchor 4, where such duplication would be only minor. | 3 / 5 |
Actionability | Commands are copy-paste ready (extract_text.py, calculate_scores.py) and the scores JSON example covers all 8 dimensions, but the flagship example is factually broken against the bundle: SKILL.md's scores.json uses snake_case keys ("problem_formulation") while scripts/calculate_scores.py matches on "Problem Formulation"-style keys, so following the example verbatim yields total_weight 0 and a final score of 0.0 with warnings. The body also points to a requirements.txt that is absent from the bundle. This lands on anchor 3 ('missing key details') rather than anchor 4 ('minor gaps'), because the documented example fails silently when executed as written. | 3 / 5 |
Workflow Clarity | Example A gives a clear numbered sequence (extract → write scores.json → calculate → produce report) with concrete commands at each step, and Example B correctly short-circuits extraction for pasted text. It stops short of anchor 5 because there are no validation checkpoints: nothing tells the user to confirm extraction produced usable text, to check the script's stderr warnings for missing dimensions, or what to do when the computed score is 0/unexpected — the report step is a one-line instruction with no feedback loop. | 4 / 5 |
Progressive Disclosure | Structure is reasonable: SKILL.md acts as an overview and points to references/evaluation_framework.md (one level deep, signaled in two places) and the two scripts, which all exist. But scored against the actual bundle, the referenced `requirements.txt` does not exist (a broken pointer in 'Dependencies'), and the 8-dimension list and 1–5 scale are inlined in SKILL.md even though they already live in the reference file — content that should be separate is inline. That combination matches anchor 3 rather than anchor 4's 'minor organization gaps'. | 3 / 5 |
Total | 13 / 20 Passed |