Content
57%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 dense, information-rich audit skill with strong actionability (output template, real commands, error handling) whose main weaknesses are repetition of its own key points, a never-explicitly-sequenced audit workflow, and a monolithic body that inlines material better split into its existing references/ pattern. The skill is functional but would improve from restructuring rather than from new content.
Suggestions
State the audit as an explicit ordered workflow (e.g., 1. fetch URL and robots.txt, 2. score the five criteria, 3. check the update ledger via the script, 4. generate GEO-ANALYSIS.md) so the sequence and checkpoints are visible rather than implied.
Move the full crawler table, the claim/bot matrix, and the llms.txt format spec into a references/ file (e.g., references/ai-crawlers.md) and keep only the recommendation and the routinely-conflated pairs in SKILL.md, mirroring the existing google-ai-optimization-guide.md pattern.
Deduplicate the training-vs-search crawler distinction and the llms.txt carries-no-weight note, which each appear three times; state each once in the crawler section and once in the output requirements.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly high-value domain data Claude cannot be assumed to know (dated statistics, crawler capability matrices), but key points are repeated: the GPTBot/OAI-SearchBot training-vs-search distinction is explained in the crawler table, again in the claim/bot table, and again in bullets; the llms.txt 'carries no weight' point appears three times. This repetition goes beyond 'minor instances that could be trimmed', placing it below the 4 anchor. | 3 / 5 |
Actionability | Concrete, executable guidance throughout: a numbered GEO-ANALYSIS.md output template, a runnable command ('scripts/claude-seo run seo_updates.py --kind product --kind core --json'), a ready-to-use llms.txt template, and an error-handling table with specific actions per failure. Not a 5 because several checks (SSR/JavaScript dependency analysis, brand mention analysis) name what to check without giving a concrete command or method for doing it. | 4 / 5 |
Workflow Clarity | The audit criteria, weighted scoring breakdown, output checklist, and error-handling paths imply a workflow, but the actual sequence (fetch URL, retrieve robots.txt, apply the five criteria, run the update ledger, generate the report) is never explicitly ordered. Not a 4 because checkpoints like 'treat a stale ledger as incomplete' exist but the step sequence itself remains implicit rather than listed. | 3 / 5 |
Progressive Disclosure | The two references (google-ai-optimization-guide.md, llmstxt-evidence.md) are real files, clearly signaled, and one level deep, but the ~400-line body inlines large blocks that belong in separate reference files: the full 15-row crawler table, the llms.txt format specification, and the platform-specific optimization tables. Not a 4 because this inline bulk is more than a 'minor organization gap'. | 3 / 5 |
Total | 13 / 20 Passed |