Content
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A highly actionable, well-structured meta-skill with strong workflow sequencing and validation checkpoints. Its main weakness is verbosity: the directory structure and Accomplish save-path guidance are repeated across multiple sections, inflating token cost.
Suggestions
Consolidate the skill anatomy / directory-tree description into a single location instead of repeating it in 'Core Principles', 'Skill Creation Process', and 'Saving Skills'.
State the Accomplish OS save paths once and reference them rather than re-listing macOS/Windows/Linux paths in both 'Saving Skills in Accomplish' and the verification steps.
Trim 'What Skills Provide' and introductory 'About Skills' text that restate concepts a capable model already knows, to better respect the token budget.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | At ~290 lines it restates the skill anatomy/directory structure multiple times (Core Principles, Skill Creation Process, Saving Skills) and re-explains the Accomplish OS paths twice; it is mostly efficient but padded with repetition and detail a competent model largely already knows. | 2 / 3 |
Actionability | It provides copy-paste-ready frontmatter templates, concrete directory trees, and explicit verification actions (e.g. 'Use the Read tool to read the SKILL.md file'), giving fully executable guidance. | 3 / 3 |
Workflow Clarity | A clear sequenced 6-step process with an explicit MANDATORY verification stage containing checkpoints (read file, verify path, validate frontmatter) and a feedback loop ('If verification fails: diagnose the issue and fix it before re-verifying'). | 3 / 3 |
Progressive Disclosure | No bundle files exist, but the single SKILL.md is well-organized into clearly headed sections with no nested references; per the rubric's simple-skill note, well-organized sections are sufficient here. | 3 / 3 |
Total | 11 / 12 Passed |