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.
An excellent operational body: lean, domain-specific, fully executable commands, and unusually strong validation checkpoints for a batch analysis. The weak spot is progressive disclosure — a key reference (`orchestration-details.md`) is cited without a resolvable path, and the analyzer script and sibling-skill dependencies sit outside the skill directory, making the bundle's file layout hard to navigate.
Suggestions
Give `orchestration-details.md` an explicit relative path (e.g., `${CLAUDE_SKILL_DIR}/references/orchestration-details.md`) as a markdown link, and place it in a `references/` directory inside the skill bundle so it is resolvable from the SKILL.md alone.
State where `content_decay.py` lives (or bundle it under `scripts/` with a one-line path note) instead of relying solely on the env-var/default fallback chain for `BLOG_SCRIPT_DIR`, which obscures the file layout.
Consider moving the extended URL-normalization guidance and the GSC API row-limit details into the reference file, keeping SKILL.md to the workflow plus a short pointer — this would shorten the front sections and strengthen the overview-to-detail split.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes Claude's competence: it never explains what Google Search Console, CTR, or quarter-over-quarter comparison are; it spends its tokens only on non-obvious domain knowledge (URL-string matching pitfalls, the 50,000-row API cap, 16-month data retention, seasonality vs. noise). Dense passages like the runtime-path rules are operational instructions, not padding; every section (workflow, live export, severity, actions) earns its place. | 5 / 5 |
Actionability | Guidance is fully executable: copy-paste bash blocks for the offline analyzer with variable resolution and absolute-path guards, concrete flag examples (--threshold 0.30, --metric impressions, --format markdown --output), exact gsc_query invocations, and explicit input-format acceptance rules (page/url, clicks, impressions, top-level rows). The only placeholders (property, YYYY-MM-DD dates) are inherently user-specific, which is standard practice, and the report's field semantics (severity tiers, needs_validation, dropped_out) are specified. | 5 / 5 |
Workflow Clarity | Both workflows (offline default, optional live export) are clearly sequenced — confirm the property, produce the two exports, run the analyzer — and this batch analysis is wrapped in explicit validation checkpoints: a pre-flight URL-normalization/same-property check, the instruction to ignore small-baseline flags, the override rule "mark them as needs_validation, not dropped_out, even if the analyzer's JSON says dropped_out" with false-drop causes (row limits, filters), error-recovery hints (check --help for normalization), and a post-hoc checklist (indexation, canonical status, query loss, links, seasonality, business value). Anchor 5 fits best; anchor 4's 'minor validation gaps' understates how many checkpoints are present. | 5 / 5 |
Progressive Disclosure | Section structure and tables are well organized, but the body's references are weakly signaled and unverifiable in the bundle: "Read the main reference `orchestration-details.md`" is given without a path or link, `content_decay.py` lives outside the skill dir via env-var-resolved `../../scripts`, and no references/, scripts/, or assets/ directories exist in this bundle at all. That matches anchor 3 ('references present but not clearly signaled') better than anchor 4, and the dense path-substitution preamble adds navigation friction. | 3 / 5 |
Total | 18 / 20 Passed |