Content
63%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 well-organized and information-rich, with a clear five-step workflow, explicit thresholds, and disciplined Lean/TOC framing, but its operational core is hollow: all referenced scripts, the intake template asset, and the three reference files are missing from the bundle, so none of the concrete commands can actually run. Fixing the bundle (or inlining the critical intake schema and one example invocation) would move this from well-written documentation to a working skill.
Suggestions
Include the referenced bundle files (scripts/process_documenter.py, scripts/bottleneck_detector.py, scripts/cycle_time_analyzer.py, assets/process_template.md, and the three references/*.md) so the documented commands and pointers resolve; alternatively inline the intake JSON schema and a runnable example in SKILL.md.
Add an explicit validation/feedback loop for the intake step — what to do when the process JSON fails validation or stage types are mis-labeled (e.g., re-confirm with the user, re-run the validator) — to raise workflow clarity.
Trim the 'Purpose' and 'Distinct from' sections, which substantially restate the description, and tighten the forcing-question library citations to reduce token overhead.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and directive — it applies Lean/TOC canon ('Subordinate everything to the constraint') rather than teaching concepts Claude already knows, and includes concrete thresholds (VA% > 25% = HEALTHY, wait > 40%, rework > 15%). Minor padding exists: the 'Purpose' failure-mode narrative and the 'Distinct from' section partially restate the description's content, keeping it below the lean anchor 5 but above anchor 3's unnecessary explanations. | 4 / 5 |
Actionability | Concrete guidance is present — 'python3 scripts/process_documenter.py --sample', '--profile (saas / services / manufacturing / healthcare)', a specified intake JSON schema, and exact detection thresholds — but every command depends on scripts/, assets/process_template.md, and references/ files that are absent from the bundle, so nothing is executable as delivered. This fits anchor 3 (concrete but incomplete, key execution details missing) rather than anchor 4, where gaps are only minor. | 3 / 5 |
Workflow Clarity | A clearly sequenced five-step flow (Intake → Map → Measure → Detect → Recommend) with explicit tool ordering ('invoke process_documenter.py → bottleneck_detector.py → cycle_time_analyzer.py in sequence') and depth-first question sequencing; step 2 notes the script validates the JSON. It falls short of anchor 5 because validation checkpoints are implicit — there is no 'if validation fails, fix and re-run' feedback loop for bad or mis-typed input data (the skill itself flags mis-labeled stage types as the most common failure). | 4 / 5 |
Progressive Disclosure | Structure is good: well-signaled one-level references ('references/lean_six_sigma_canon.md — TIMWOOD wastes, value-stream mapping...') with per-file content summaries, and the body stays an overview. However, none of the seven referenced bundle files (3 scripts, 3 references, 1 asset) actually exist in the bundle, so every pointer is dangling and disclosure cannot progress — matching anchor 3 (structure present but organization broken) rather than anchor 4 (most content appropriately placed and reachable). | 3 / 5 |
Total | 14 / 20 Passed |