Content
75%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 highly actionable, well-structured skill: every method comes with executable tooling that matches the real bundled script, concrete numeric thresholds, and a report template. Its weaknesses are moderate redundancy of textbook material Claude already knows (basic PERT statistics, FPA definitions) and the absence of an explicit validate-and-revise loop in the estimation workflow.
Suggestions
Trim the explanations of concepts Claude already knows — the Variance/σ² definitions, the 'Where: O/M/P' definitions, and the 68/95/99.7 confidence-interval table — keeping only the decision rule of which interval to use for which audience.
Add an explicit feedback loop to the PERT steps, e.g., 'If spread ratio (P/O) > 4, return to the user to clarify requirements before finalizing the estimate,' so the rules of thumb act as checkpoints rather than commentary.
Move the FPA DET/RET complexity matrices and the T-shirt conversion tables into a references/ file (e.g., references/fpa-tables.md), keeping SKILL.md as an overview that links to them one level deep.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Much of the body is genuinely useful reference data (FPA weight matrices, T-shirt size tables, adjustment-factor percentages), but it also explains concepts Claude already knows: 'Variance V = σ²', a confidence-interval table restating the empirical rule (68.3% = ±1σ, 95% = ±2σ), and definitions like 'O (Optimistic): Shortest duration assuming everything goes smoothly'. Mostly efficient with some unnecessary explanation that could be tightened, matching anchor 3 rather than the noticeably-padded anchor 2 or the minor-trim anchor 4. | 3 / 5 |
Actionability | The three script invocations for PERT, tshirt, and fpa are copy-paste ready with complete JSON payloads, and I verified the bundled scripts/estimate_calculator.py implements exactly these flags and value tables. Together with the method-selection table, concrete thresholds (e.g., 'O should not be less than 30% of M'), and a fill-in output template, the common cases are fully covered — the top anchor. | 5 / 5 |
Workflow Clarity | The Quick Start gives a clear 4-step sequence, each method has numbered steps, and the O/M/P rules of thumb and adjustment-factor checklist function as verification checkpoints. However, there is no explicit feedback loop (e.g., 'if spread ratio > 4, clarify requirements and re-estimate'), so it fits anchor 4 (most checkpoints present, minor gaps) rather than anchor 5's explicit validate-then-retry pattern. | 4 / 5 |
Progressive Disclosure | The single bundle file (scripts/estimate_calculator.py) is clearly signaled with executable usage in two places, and the body is well-sectioned with a navigation-friendly method-selection table up front. Scored against the actual bundle (one script, no references/), the remaining gap is that ~290 lines of FPA DET/RET lookup matrices and T-shirt conversion tables are inlined where a references/ file would keep the overview lean — good structure with minor organization gaps, i.e., anchor 4 not 5. | 4 / 5 |
Total | 16 / 20 Passed |