Content
88%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 a highly actionable, well-sequenced workflow with concrete commands, an exact data schema, and explicit validation feedback loops, assuming Claude's competence while staying specific to the brand-extraction domain. Its main weakness is moderate verbosity from repeated safety-net caveats and the inline question-form, and the absence of progressive file-based references.
Suggestions
Trim the repeated 'safety net is no substitute' caveats in the logo and imagery bullets to a single concise note, since they restate the same point.
Consider hoisting the full brand.json schema and/or the anti-bot `<question-form>` into a referenced file (e.g. references/brand-schema.json) so the main SKILL.md stays a lean overview and progressive disclosure can score higher.
Tighten the finalize paragraph, which runs as one long sentence enumerating every module and asset tile; a short list or a pointer to detail would reduce padding.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense with actionable, skill-specific detail (semantic color roles, exact brand.json shape, finalize command) and largely avoids generic over-explanation, though the long callouts repeating the 'safety net is no substitute' caveat and the anti-bot question-form add padding that could be tightened. It is noticeably above the midpoint but not fully lean. | 4 / 5 |
Actionability | Provides fully executable guidance — concrete agent-browser subcommands, an exact copy-paste brand.json schema with real values, the `od brand preview` and `od brand finalize` commands, and a literal `<question-form>` block — covering the common cases copy-paste ready. | 5 / 5 |
Workflow Clarity | A clearly sequenced three-step chain (Measure → Synthesize → Build & register) with explicit validation checkpoints: snapshot before extracting, preview after each field group, and re-run finalize if validation errors are reported, plus an error-recovery feedback loop. | 5 / 5 |
Progressive Disclosure | The content is well-structured into clearly signaled sections (the three steps, anti-bot handling, hard rules, safety) and keeps the large brand.json example inline rather than burying references, but there are no bundle files or one-level-deep external references to navigate, so it is well-organized without the clear overview→reference split that would earn a 5. | 4 / 5 |
Total | 18 / 20 Passed |