Content
100%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 an exemplary compact skill document: every token earns its place, guidance is fully executable, the single-step workflow includes typed error feedback, and the bundle structure is appropriately minimal with a verified script reference.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The ~35-line body is lean bullet-point guidance with zero padding and no explanation of concepts Claude already knows (no SPARQL primer, no library comparisons). Every section — rules, input, output, execution, references — earns its place. | 5 / 5 |
Actionability | The body provides a copy-paste-ready command (`echo '{"query":"ASK {"}' | python scripts/sparql_request.py`), a complete list of required and optional input fields verified against the real script, documented output/error shapes, and two concrete JSON examples covering the common ASK and SELECT cases. | 5 / 5 |
Workflow Clarity | A simple single-purpose skill whose one action is unambiguous: pipe a JSON request to the script and get a summary or a typed error. Error codes (invalid_json, network_error, invalid_response) plus the "re-run requests instead of relying on older tool output" rule give explicit feedback; no destructive or batch operations, so no validation cap applies. | 5 / 5 |
Progressive Disclosure | Under 50 lines, well-organized headed sections, and the sole reference (scripts/sparql_request.py) exists in the bundle and is one level deep. The References section explicitly bounds the package to SKILL.md plus that script, so nothing is buried or nested. | 5 / 5 |
Total | 20 / 20 Passed |