Content
81%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 strong, highly actionable skill body with executable commands, prerequisites, and an excellent false-positive verification workflow. The main weaknesses are redundancy in the language-specific Quick Start examples and a reference structure whose target files could not be verified in the provided bundle.
Suggestions
Consolidate the VM-compiled and Swift Quick Start subsections into the language-specific reference files to remove command examples that duplicate the main Quick Start.
Add a brief mention of ct_analyzer/analyzer.py's location and role alongside the references table so every referenced path is discoverable.
Trim the macOS PATH setup detail, which is already deferred to references/vm-compiled.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly tables and copy-paste commands, but the VM-compiled and Swift subsections re-run the same analyzer.py invocation already shown in Quick Start, and PATH/setup detail duplicates what is deferred to references/vm-compiled.md. Matches anchor 3 ('Mostly efficient but includes some unnecessary explanation or could be tightened') rather than 4 because of this repeated per-language redundancy. | 3 / 5 |
Actionability | Fully executable guidance throughout: concrete commands with all flags (--warnings, --func, --json, --arch, --opt-level), a prerequisites table with install commands (e.g. 'dotnet tool install -g ilspycmd'), worked false-positive code examples, and a problem/detection/fix table. Matches anchor 5 ('Fully executable; copy-paste ready code or commands; specific examples cover the common cases'). | 5 / 5 |
Workflow Clarity | The process flows clearly from language selection and prerequisites through running the tool, interpreting PASSED/FAILED, and verifying results. The 'Verifying Results' section provides explicit validation with numbered steps ('Identify the secret inputs', 'Trace data flow'), a triage-question checklist, and true/false-positive classification — matching anchor 5 (explicit validation steps, feedback loops, checklists). This is read-only analysis, so the destructive/batch cap does not apply. | 5 / 5 |
Progressive Disclosure | One-level-deep references are well-signaled via the Language Selection table (references/compiled.md, references/swift.md, etc.) with detailed setup correctly deferred to references/vm-compiled.md. Minor gaps keep it at anchor 4 rather than 5: the ct_analyzer/analyzer.py script is not covered by any reference listing, no bundle files were provided to verify the referenced paths exist, and some per-language Quick Start content overlaps what belongs in the language-specific reference files. | 4 / 5 |
Total | 17 / 20 Passed |