Content
81%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 well-structured operational skill body: every workflow is sequenced with explicit validation checkpoints, templates and checklists are directly usable, and detail is properly pushed to one-level-deep reference files. The weaknesses are moderate verbosity (redundant decision trees, dated fee figures) and an unreferenced bundle script.
Suggestions
Remove the ASCII "FDA Pathway Selection" and "EU MDR Classification" decision trees or the overlapping Pathway Selection Matrix / Pre-Sub decision tables — they encode the same logic twice.
Move time-sensitive figures (2024 user fees, MDUFA timeline dates, dated sample output) into the relevant reference files, or mark them with a check-current-fee note, so the SKILL.md body does not silently go stale.
Add scripts/regulatory_pathway_analyzer.py to the Tools table with a one-line purpose and usage example (as done for regulatory_tracker.py) so the bundle's larger script is discoverable.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient, dense domain reference material, but there is tightening to do: the ASCII decision trees ("Is predicate device available?...") duplicate the Pathway Selection Matrix and Pre-Sub decision table; the "Regulatory Tracker Features" bullet list restates the tool table's purpose; and time-sensitive figures ("User Fee ~$22K (2024)", "~$135K", "~$440K", "2024-11-01" in the sample output) sit outside any staleness-tolerant section and will drift. Fits anchor 3 rather than 4 because several sections could be trimmed or are padded relative to their value. | 3 / 5 |
Actionability | Fully actionable throughout: fill-in-ready templates (Regulatory Strategy, Impact Assessment), a 9-section 510(k) checklist, a worked Substantial Equivalence comparison example with real values ("±2mm vs ±3mm predicate"), a GSPR checklist row example, and a real script with copy-paste usage ("python regulatory_tracker.py --report status") plus sample output. Specific examples cover the common cases, matching anchor 5. | 5 / 5 |
Workflow Clarity | All five workflows use a numbered 1–8 sequence ending in an explicit **Validation** checkpoint (e.g., "Validation: Submission accepted; MDUFA date received; tracking system updated"), with checklists for complex processes and error-recovery guidance via the deficiency-prevention table ("Common FDA Deficiencies and Prevention") and escalation criteria. This matches anchor 5's explicit-checkpoint, checklist, and recovery-loop pattern; anchor 4 would require missing checkpoints, which are present in every workflow. | 5 / 5 |
Progressive Disclosure | Good structure: four real, one-level-deep reference files clearly signaled both inline ("See: references/fda-submission-guide.md") and in a References table with content descriptions; no nested references. The gap is that scripts/regulatory_pathway_analyzer.py — the larger of the two scripts — exists in the bundle but is never referenced in SKILL.md, leaving it undiscoverable. Fits anchor 4 ('minor organization gaps') rather than 5. | 4 / 5 |
Total | 17 / 20 Passed |