Content
92%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-engineered, highly actionable skill body: executable commands for every capture mode, a sequenced workflow with validation and error-recovery guidance, and clean separation into a real, one-level-deep reference file. The only weakness is mild redundancy between the Workflow and Capture Defaults sections.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes competence — no concept explanations of what Codex, Claude Code, or mitmproxy are. Minor trimming is possible: the capture scripts are introduced in Workflow step 4 and then re-covered in Capture Defaults, and a few sentences ('Treat state diffs as sensitive local artifacts too...') restate adjacent rules. | 4 / 5 |
Actionability | Commands are copy-paste ready: `command -v` discovery, mkdir output dirs, fully-argued invocations of run_with_mitm.sh, run_tmux_capture.sh, and capture_state.py snapshot/diff, plus a JSON recording template. Common cases (codex headless, claude-code tmux, interactive TUI) each get a concrete example. | 5 / 5 |
Workflow Clarity | The 8-step Workflow is clearly sequenced from feature definition through capture, fact extraction, implementation, testing, and handoff. Validation is explicit (step 7 tests/smoke command, Done Criteria checklist), and error recovery is present ('If TLS fails, read the certificate notes... and fix trust before interpreting missing traffic as product behavior'). | 5 / 5 |
Progressive Disclosure | The SKILL.md stays an overview and delegates depth to a clearly signaled, one-level-deep reference ('Read references/capture-workflow.md before running capture for the first time'), which exists and does not nest further. All referenced bundle files exist; llm_dump.py is an internal helper invoked by run_with_mitm.sh rather than an orphan. | 5 / 5 |
Total | 19 / 20 Passed |