Content
92%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 SKILL.md body is a strong example: executable, well-sequenced with an explicit auth-validation checkpoint and error-recovery table, and cleanly split from its implementation script. The only weakness is mild duplication between the Python CLI usage and the inline curl API reference.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean — concrete setup steps, executable commands, example outputs, and a compact troubleshooting table — with only minor trimmable content, e.g., the '## API Reference (curl)' section largely duplicates what the bundled Python script already does. This matches the score-4 anchor 'Efficient; minor instances of over-explanation that could be trimmed'; it is not 5 because of that curl duplication, and not 3 because there is no padding or explanation of concepts Claude already knows. | 4 / 5 |
Actionability | Everything is copy-paste ready: numbered token-generation steps ('Account → Settings ... + New Access Token'), exact env-var block, runnable commands ('$CANVAS list_assignments 12345 --order-by due_at'), concrete JSON output examples, and curl equivalents. This matches the score-5 anchor 'Fully executable; copy-paste ready code or commands; specific examples cover the common cases'. It is not 4 because there are no gaps — even edge cases (empty course list, wrong institution) are covered in Troubleshooting. | 5 / 5 |
Workflow Clarity | The single-purpose read-only workflow is unambiguous: a numbered setup sequence, an explicit first-use validation checkpoint ('On first use, verify auth by running $CANVAS list_courses — if it fails with 401, guide the user through setup'), and error-recovery guidance in the Troubleshooting table. This matches the score-5 anchor 'Clear sequence with explicit validation steps; feedback loops for error recovery'. It is not 4 because validation and recovery paths are explicit, not merely implied. | 5 / 5 |
Progressive Disclosure | The body is a clear, well-sectioned overview; the 160-line implementation is correctly externalized to 'scripts/canvas_api.py', which exists in the bundle and is accurately described ('Python CLI for Canvas API calls'); no buried or nested references. This matches the score-5 anchor 'Clear overview with well-signaled one-level-deep references; content appropriately split; easy navigation'. It is not 4 because there are no organization gaps — every inline section (setup, usage, output, rules, troubleshooting) belongs inline at this skill's size. | 5 / 5 |
Total | 19 / 20 Passed |