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 dense, well-structured skill body that balances executable connector commands with a clear 9-step workflow, explicit decision gates, and tidy one-level reference disclosure. Minor conciseness trimming would push it to the top of the scale.
Suggestions
Trim contextual framing sentences (e.g. 'As of 2026, robots.txt must make explicit decisions about AI engines') to keep the body purely instructional.
Consolidate the connector command catalog in Data Sources into a short table or move the longer recipes into a reference file to reduce in-body token weight.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly lean and actionable, assuming Claude's knowledge with no generic padding; a few contextual asides ('As of 2026, robots.txt must make explicit decisions about AI engines') could be trimmed without losing value. | 4 / 5 |
Actionability | Provides copy-paste-ready commands throughout — psi.py/ledger.py piping, crt.sh curl recipe, indexpush.py with env-var gating — plus concrete thresholds (LCP <2.5s, INP <200ms, CLS <0.1) covering the common audit cases. | 5 / 5 |
Workflow Clarity | A clearly sequenced 9-step audit with per-step evidence/issues/fixes/score, explicit Decision Gates (stop-vs-continue), and validation discipline (Measured/User-provided/Estimated/N/A) plus dry-run gating on the mutation/bulk paths. | 5 / 5 |
Progressive Disclosure | SKILL.md is a well-organized overview with clearly signaled, one-level-deep references to eight real reference files (playbooks, templates, examples), each split appropriately with a consolidated Reference Materials nav section. | 5 / 5 |
Total | 19 / 20 Passed |