Content
86%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 exemplar of lean, well-structured skill content: operational bullets, concrete field lists, an executable example, and a verified shallow script reference with no padding. The only gaps are a non-trivial evidence-retrieval example and an explicit validate-on-failure checkpoint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and operational — short bullets covering rules, input fields, output shape, and one executable command with zero concept explanation (no 'what is GraphQL/CIViC' padding); every token earns its place, matching the 'lean and efficient; assumes Claude's competence' anchor. | 5 / 5 |
Actionability | Provides a copy-paste bash command, explicit input/output field lists, and two concrete JSON query patterns — 'mostly executable guidance; concrete code or commands with minor gaps'; not a 5 because both example queries are trivial schema-introspection (`__typename`, `__schema`) rather than a real targeted evidence-retrieval example. | 4 / 5 |
Workflow Clarity | As a simple single-task skill the invocation path is clear (stdin JSON → script → summary), and the Output section documents success vs failure; not a 5 because the failure handling is informational ('Failure returns ok=false with error.code ...') rather than an explicit validation checkpoint instructing Claude to check `ok` and surface `error.code` before summarizing. | 4 / 5 |
Progressive Disclosure | Under 50 lines with well-organized sections (Operating rules, Execution behavior, Input, Output, Execution, References) and a single one-level-deep reference to `scripts/civic_graphql.py` that exists in the bundle, matching the simple-skill exception for a clear overview with well-signaled shallow references. | 5 / 5 |
Total | 18 / 20 Passed |