Content
82%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-organized, highly actionable skill body built around a real bundled tool and reference file, with clear workflows and authorization/OPSEC checkpoints. The main improvement room is tightening the intro and moving more reference-grade tables into the existing reference file.
Suggestions
Trim the opening paragraph — it restates the frontmatter description; lead directly with the skill's distinctive purpose or the authorization gate.
Move the full 'Technique Scoring Reference' and 'Attack Path Graph Construction' tables into references/attack-path-methodology.md, keeping only the formula and one short example inline in SKILL.md.
Add an explicit validate→fix→retry feedback loop for engagement_planner.py runs (e.g., on exit code 1 or 2, inspect the error, adjust techniques/scope, re-run) to raise workflow_clarity to 5.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient — tables, formulas, and copy-paste commands that assume Claude's security knowledge without explaining what MITRE ATT&CK or LSASS is — but the opening paragraph re-derives the description's framing and several reference tables (effort formula, attack-path graph) overlap content offloaded to the reference file. | 4 / 5 |
Actionability | Provides fully executable, copy-paste-ready invocations of engagement_planner.py with concrete flags, access levels, and exit codes across three workflows, plus a defined scoring formula and specific technique tables that cover the common cases. | 5 / 5 |
Workflow Clarity | Three workflows are clearly sequenced (numbered steps, week-by-week phases, the kill-chain ordering principle, and the OPSEC checklist as a per-phase gate), with verification via the --authorized gate, exit codes, and detection-event logging; minor gap is the absence of an explicit validate→fix→retry feedback loop for plan generation failures. | 4 / 5 |
Progressive Disclosure | Well-structured with a table of contents and clearly signaled one-level-deep references to the real references/attack-path-methodology.md and scripts/engagement_planner.py bundle files; the main body is somewhat long with several inlined reference tables that could live in the reference file, keeping it just short of the lean overview ideal. | 4 / 5 |
Total | 17 / 20 Passed |