Content
61%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 advisory skill with genuinely additive domain expertise (benchmarks, diagnostic questions, red flags) and verified, runnable script entry points. Its weaknesses are a redundant Keywords section that inflates token cost, an implied rather than explicit workflow with no validation checkpoints, and script invocations that omit the input data format needed to run them on real data.
Suggestions
Delete or drastically trim the Keywords section — it duplicates the frontmatter description's trigger terms and consumes tokens without instructing Claude anything.
State the scripts' input contract inline: CSV column format (deal_id, name, stage, arr_value, close_date...) and key flags (--csv, --scenario, --period), so Claude can gather and pass real data without opening the script source.
Add a short numbered workflow (read company-context.md → diagnostic questions → select framework/run script → apply Communication output format → sanity-check forecast against actuals) to make the implicit sequence explicit and add a validation checkpoint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly dense, additive domain content (benchmark tables, diagnostic questions), but the ~40-item Keywords section ("CRO, chief revenue officer, revenue strategy, ARR, MRR, sales model, pipeline...") largely duplicates the frontmatter description's triggers, and the ARR waterfall / NRR formula ("NRR = (Opening + Expansion - Contraction - Churn) / Opening") re-derives concepts Claude already knows. Not 2 — only these spots are redundant and nothing is generic library-style padding; not 4 — the Keywords section alone is a substantial token cost with no instructional value. | 3 / 5 |
Actionability | Copy-paste-runnable commands ("python scripts/revenue_forecast_model.py", confirmed to run with no args), specific thresholds ("Pipeline Coverage 3x+ quota", "Magic Number > 0.75"), defined formulas, and a concrete Output Artifacts table ("'Forecast next quarter' → Pipeline-based forecast with confidence intervals"). Not 5 — the body never states the scripts' CSV input format or flags (--csv, --scenario), so Claude can't prepare input data without opening the script docstrings; common cases aren't self-contained in the skill. | 4 / 5 |
Workflow Clarity | A sequence exists but is only implicit: "Ask these before any framework", "Always read company-context.md before responding", then framework/script and the Communication output format. No numbered or explicitly ordered workflow ties these together, and there are no validation checkpoints (e.g., reconcile forecast vs. actuals before presenting). Matches the 3 anchor (sequence present, checkpoints missing/implicit); not 4 because the ordering must be inferred from scattered sections rather than a stated flow. | 3 / 5 |
Progressive Disclosure | Bundle structure is real and well-wired: the Resources section and the Core Responsibilities table both point to the three actual files in references/ and two in scripts/, all one level deep with no nesting. Not 5 — reference pointers are duplicated across two sections, "see ../agent-protocol/SKILL.md" navigates outside the bundle, and sizable inlined benchmark tables (Revenue Metrics, NRR Benchmarks) could partly live in the references. | 4 / 5 |
Total | 14 / 20 Passed |