Content
78%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.
An exemplary overview-style SKILL.md: terse, command-driven, with a verified one-level-deep reference bundle and a working troubleshooting/feedback table. The main gaps are the redundant When-to-Use table and the absence of any inline executable content for the core policy-application workflow.
Suggestions
Drop or merge the 'When to Use This Skill' table with the frontmatter triggers it duplicates, saving ~10 lines of redundant body tokens.
Inline one minimal runnable policy snippet (e.g., token-limit + semantic-cache lookup) in 'Apply AI Governance Policy' so the core task is executable without a file hop, keeping the full combinations in policies.md.
Add an explicit checkpoint line after 'Add AI Backend' and the curl test (e.g., 'verify a 200 and backend list before layering policies') to make the existing validation steps sequential rather than implied.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean body with no concept explanations — commands and tables dominate, and every section earns its place. Not a 5 because of redundancy: the 'When to Use This Skill' table repeats the frontmatter triggers almost verbatim, and the Quick Reference policy listing partially duplicates policies.md's own quick-decision table. | 4 / 5 |
Actionability | Concrete, copy-paste-ready az and curl commands for gateway inspection, endpoint testing, and backend creation, with real flag values and JSON payloads. Not a 5 because the central 'Apply AI Governance Policy' task gives only an ordered intent list and defers entirely to references/policies.md, so the most common workflow has no inline executable artifact. | 4 / 5 |
Workflow Clarity | Sequences are clear (discover → create backend → grant RBAC; a numbered policy placement order), with a 'Test AI Endpoint' verification command and a troubleshooting table mapping errors to fixes. Not a 5 because inline checkpoints are implicit — the body never states 'verify the backend list/curl succeeds before applying policies', and the full validated sequences live in patterns.md rather than the body. | 4 / 5 |
Progressive Disclosure | Model progressive disclosure: a concise overview with every detailed policy, pattern, and SDK reference one level deep and clearly signaled, all linked paths and anchor targets verified to exist (policies.md, patterns.md, troubleshooting.md, four SDK quick-refs), organized by category with a navigation table. The single second-hop link (auth-best-practices.md from the SDK refs) is a supplementary detail, not a buried instruction chain. | 5 / 5 |
Total | 17 / 20 Passed |