Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A thorough, highly actionable skill body with clear sequenced workflows and explicit validation gates, but it is over-long for the budget it itself prescribes and contains several dangling references to bundle paths (agents/*.md, eval-viewer/generate_review.py) that are absent from the actual bundle.
Suggestions
Fix dangling references: the bundle has no agents/ directory, so 'agents/grader.md', 'agents/comparator.md', and 'agents/analyzer.md' should either be added under references/ (or wherever they live) or the paths corrected; likewise replace 'eval-viewer/generate_review.py' with the actual 'scripts/generate_report.py'.
Trim conversational filler to respect the token budget the skill itself advocates — remove 'Cool? Cool.', the plumbers/parents anecdote, the 'billions a year in economic value' aside, 'Good luck!', and the final verbatim re-statement of the core loop already covered above.
Consolidate the repeated core-loop summaries (opening list, mid-body restatements, and closing 'Repeating one more time' section) into a single concise statement to reduce redundancy.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The ~480-line body is mostly efficient and assumes Claude's competence (no explaining what libraries/PDFs are), but carries notable conversational padding — 'Cool? Cool.', the 'plumbers opening terminals / parents googling npm' anecdote, '(we are trying to create billions a year in economic value here!)', 'Good luck!', and a verbatim re-statement of the core loop at the end. Not a 3 because these tokens do not earn their place; not a 1 because it never explains basic concepts Claude already knows. | 2 / 3 |
Actionability | Provides copy-paste-ready, fully specified commands — 'python -m scripts.aggregate_benchmark <workspace>/iteration-N --skill-name <name>', 'nohup python <skill-creator-path>/eval-viewer/generate_review.py ... --static <output_path>', 'python -m scripts.run_loop --eval-set ... --max-iterations 5' — plus exact JSON shapes and exact field names ('text', 'passed', 'evidence'). Not a 2 because the guidance is concrete and executable, not pseudocode or abstract. | 3 / 3 |
Workflow Clarity | The eval/iteration workflows are clearly sequenced (Step 1–5: spawn runs, draft assertions, capture timing, grade, aggregate+launch viewer) with explicit gating checkpoints — 'Do NOT generate the viewer or benchmark until grading.json exists for every run', 'always run the grader first', and a repeat loop with explicit stop conditions. Not a 2 because validation checkpoints and feedback loops are explicit rather than implicit. | 3 / 3 |
Progressive Disclosure | Content is split across real, one-level-deep, clearly signaled files (references/schemas.md, assets/eval_review.html, scripts/*), but the body repeatedly points at paths that do not exist in the bundle — 'agents/grader.md', 'agents/comparator.md', 'agents/analyzer.md' (no agents/ directory) and 'eval-viewer/generate_review.py' (the actual file is scripts/generate_report.py). Not a 3 because following this navigation would fail; not a 1 because genuine structure exists and several referenced files do resolve. | 2 / 3 |
Total | 10 / 12 Passed |