Content
71%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-engineered composite workflow with a deterministic scoring model, explicit human checkpoints, and thorough edge-case handling — genuinely actionable throughout. Its main weaknesses are length-driven inline bloat (config schema and CSV spec belong in reference files) and the absence of a worked example or final output verification step.
Suggestions
Move the full ICP config JSON schema and the CSV column specification into reference files (e.g., references/config-schema.md, references/csv-spec.md), keeping only a minimal example inline in SKILL.md.
Add one worked example showing a single lead flowing through Steps 3-6 to a composite score and verdict, which would make the scoring logic concrete.
Add a final validation step in Step 7 (e.g., re-reading the CSV to confirm column completeness and verdict/score consistency) to close the workflow's feedback loop.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is largely instruction-dense and assumes competence (e.g., 'a "Director" at a 10-person startup ≠ "Director" at a 10,000-person enterprise') without explaining concepts Claude already knows. It is not 5 because the ~55-line config JSON template and the CSV column enumeration partially duplicate the per-step output blocks and could be tightened. It is not 3 because unnecessary explanation is limited to isolated spots rather than a consistent pattern. | 4 / 5 |
Actionability | The guidance is almost fully executable for an instruction-only skill: a weighted scoring table with numeric mappings ('Company Size 15%: match=100, borderline=50'), explicit verdict thresholds ('Score ≥ 75: qualified'), hard overrides, enum values, and concrete JSON output blocks plus a summary report template. It is not 5 because there is no worked input-to-output example of a scored lead, and not 3 because nothing is pseudocode or vague. | 4 / 5 |
Workflow Clarity | A clear 7-step sequence with an architecture diagram, an explicit 'Human Checkpoint' in Step 1, a data gap report, and an 'insufficient_data if >3 dimensions unknown' rule provide real validation checkpoints for this batch operation. It is not 5 because there is no final verification step for the output CSV itself, and not 3 because checkpoints for the riskiest phase (data gaps before qualification) are explicit rather than implicit. | 4 / 5 |
Progressive Disclosure | The content is well-sectioned but entirely monolithic: the full config schema, per-dimension qualification rubrics, scoring table, and CSV column reference are all inlined in a ~450-line SKILL.md with no bundle files to offload any of it. It is not 4 because content that clearly belongs in separate reference files (the config schema, the CSV column spec) is inline; it is not 2 because section structure is clean and navigable. | 3 / 5 |
Total | 15 / 20 Passed |