Content
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is well-organized and concrete for an analysis methodology, but it is a dense single-file wall with illustrative tables that inflate token cost and lacks executable code and explicit validation checkpoints.
Suggestions
Move the full valuation-trap table, reference WACC/EV-EBITDA ranges, and the output-format template into separate reference files, keeping SKILL.md a lean overview.
Tighten or trim the worked example tables (5-year FCFF projection and sensitivity matrix) to one compact illustrative row/column, since Claude already understands these mechanics.
Add an explicit validation checkpoint to the DCF workflow (e.g., sanity-check that WACC > g and that the terminal value is <75% of enterprise value before trusting the output).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and assumes competence without explaining basic concepts, but the full FCFF projection table, sensitivity matrix, and output template pad the token budget beyond what Claude needs for a methodology it largely already knows. | 2 / 3 |
Actionability | Concrete formulas, parameter ranges, and a decision tree are provided, but the guidance is math notation and reference values rather than executable, copy-paste-ready code. | 2 / 3 |
Workflow Clarity | A clear method-selection decision tree and cross-validation procedure exist, but the DCF steps lack explicit validation checkpoints or error-recovery feedback loops. | 2 / 3 |
Progressive Disclosure | A single monolithic file holds everything inline — the trap table, full output template, and reference ranges could be split into separate reference files — though headings provide reasonable internal organization. | 2 / 3 |
Total | 8 / 12 Passed |