Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is highly actionable with a clear, validated multi-step workflow and strong security framing. It loses points on conciseness due to repeated reminders and dense inline GraphQL, and on progressive disclosure because everything lives inline with no reference files.
Suggestions
Move the large GraphQL pagination snippets into a references/ file and link to it, keeping the SKILL.md body lean.
Consolidate the repeated prompt-injection / external-data reminders into a single concise security note to reduce token overhead.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient and instruction-oriented, but the repeated security/prompt-injection reminders and the lengthy embedded GraphQL pagination blocks add bulk that could be tightened or offloaded to a reference. | 2 / 3 |
Actionability | Provides copy-paste-ready, executable gh/GraphQL/bash commands at every step with concrete jq filters, test commands, and decision matrices — fully actionable. | 3 / 3 |
Workflow Clarity | An explicit 8-step sequenced workflow with validation checkpoints (verify against bash, run tests, iterate until passing) and clear feedback loops for error recovery. | 3 / 3 |
Progressive Disclosure | The SKILL.md is a long monolithic body with no bundle files in references/scripts/assets and no one-level-deep references to split out the heavy GraphQL snippets; some inline content could be separated for easier navigation. | 2 / 3 |
Total | 10 / 12 Passed |