Content
77%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 CAPA playbook with concrete templates, quantitative thresholds, decision trees, and explicit validation checkpoints with feedback loops. The main defect is packaging: every referenced bundle file (two reference guides and the tracker script) is missing, leaving dangling pointers and commands that cannot run.
Suggestions
Progressive disclosure: ship the referenced bundle files (references/rca-methodologies.md, references/effectiveness-verification-guide.md, scripts/capa_tracker.py) or inline their critical content — all three pointers are currently dangling.
Actionability: if scripts/capa_tracker.py cannot be bundled, replace the bash invocation examples with a self-contained description of the input JSON schema and the computed outputs so the guidance is executable without the missing script.
Conciseness: keep either the generic 5-Why template or the fully worked calibration example — the worked example alone conveys the pattern, so dropping the blank template roughly halves that section's token cost.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense with non-generic operational data Claude would not reliably know ("First-time effectiveness | >90%", "Critical | 30 days | 30-90 days post-implementation", "8.5.2 Corrective Action | Eliminate cause of nonconformity"). Minor over-explanation keeps it from 5: the generic 5-Why template block ("WHY 1... EVIDENCE: [Supporting data]" x5) is immediately followed by a full worked example, and the 6M fishbone table largely restates standard categories. Not 3 because nearly every section is specific operational content rather than padding. | 4 / 5 |
Actionability | Concrete fill-in templates ("ACTION 1: [Specific action description]... Success Criteria: [Measurable outcome]"), copy-paste commands ("python scripts/capa_tracker.py --capas capas.json"), a complete JSON input example, and ASCII decision trees make the guidance mostly executable. Not 5 because the tracker commands depend on scripts/capa_tracker.py, which is not present in the bundle, so they cannot actually run as packaged. | 4 / 5 |
Workflow Clarity | Each phase is a numbered sequence with an explicit validation checkpoint ("**Validation:** Root cause explains all symptoms; if eliminated, problem would not recur"), evidence checklists ("Root cause can be verified with objective evidence"), and error-recovery feedback loops ("Yes → CAPA INEFFECTIVE (re-investigate root cause)"). This matches the top anchor: clear sequence, explicit validation, feedback loops, and checklists for a complex multi-phase process. | 5 / 5 |
Progressive Disclosure | In-body structure is good — a table of contents and clearly signaled one-level-deep pointers ("See `references/rca-methodologies.md` for complete method details and templates"). However, none of the referenced files exist in the bundle: references/rca-methodologies.md, references/effectiveness-verification-guide.md, and scripts/capa_tracker.py are all missing, so the deeper disclosure levels are unreachable. Not 4 because dangling references to three files are more than a minor organization gap; not 2 because the body's own structure is well-organized and references are one level deep and clearly signaled. | 3 / 5 |
Total | 16 / 20 Passed |