Content
92%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.
A well-structured, highly actionable body that practices what it preaches: hard rules stated up front, exact commands with expected output, validation and feedback loops in both workflows, and detail correctly offloaded to real, one-level-deep reference files. The only weakness is mild — an introductory definition and folder-tree explanation that an already-capable agent could partly infer.
Suggestions
Trim the opening paragraph defining what a skill folder is and compress the folder-tree/progressive-disclosure explanation to two or three lines, trusting the reader's familiarity with the concept.
The Step 1 category list (document/asset creation, workflow automation, MCP enhancement) could move to references/patterns.md alongside the other structural patterns, shortening the body's decision overhead.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense with earned tokens — rules, hard requirements, weak/strong examples, and a checklist — and pushes detail (frontmatter fields, patterns, testing templates) into references/. However, minor instances could be trimmed: the opening definition of what a skill folder is ('A skill is a folder that teaches an agent how to handle a specific task or workflow') and the folder-tree explanation of progressive disclosure cover ground an agent in this harness can largely infer. Not a 3 ('several unnecessary explanations') — the padding is at most one or two sentences; not quite a 5 ('every token earns its place'). | 4 / 5 |
Actionability | Guidance is fully executable: the exact validator command 'python scripts/validate_skill.py /path/to/your-skill-name' with expected output ('PASS with 0 errors'), a concrete frontmatter template, a concrete weak-vs-strong description example, a literal debugging prompt to ask the agent, data dependencies between steps, and a pre-delivery checklist. This is copy-paste-ready and covers the common cases, matching the anchor-5 standard. | 5 / 5 |
Workflow Clarity | Both workflows are clearly sequenced with numbered steps and explicit validation checkpoints: Step 5 runs the validator with expected output, the review workflow starts by running the validator and maps failure modes to fixes, and Step 6 defines a feedback loop (iterate on a single challenging task until it succeeds, then extract the winning approach). A Quick Checklist backstops the whole process. Not a 4: there are no missing checkpoints. | 5 / 5 |
Progressive Disclosure | Verified against the actual bundle: all referenced files exist (references/frontmatter.md, references/patterns.md, references/testing.md, scripts/validate_skill.py), references are one level deep and clearly signaled ('For all optional fields... read references/frontmatter.md'), and detail is appropriately split out while the body stays an overview. This matches the anchor-5 pattern of a concise overview with well-signaled, one-level-deep pointers. | 5 / 5 |
Total | 19 / 20 Passed |