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.
The content is well-structured and highly actionable with executable commands, a clear sequenced workflow, and a real one-level-deep reference. It is held back only by minor conciseness trim opportunities, implied rather than explicit inline validation checkpoints, and one unreferenced bundle script.
Suggestions
Add an explicit inline validation checkpoint in the workflow (e.g., after capture, verify the trace and state-diff exist before moving to implementation) to strengthen the feedback loop.
Reference scripts/llm_dump.py in the body or remove it from the bundle so every bundle file is discoverable from SKILL.md.
Trim explanatory prose such as the mitm proxy/CA sentence and the default-repo guidance to tighten token efficiency.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is efficient and assumes Claude's competence without explaining known concepts, but a few prose sentences (e.g., the mitm proxy/CA explanation, the default-repo guidance) could be trimmed, keeping it just short of fully lean. | 4 / 5 |
Actionability | It provides copy-paste-ready shell commands covering the common cases — `command -v` discovery, mkdir + run_with_mitm.sh, tmux capture, and full capture_state.py snapshot/diff invocations with concrete arguments and flags. | 5 / 5 |
Workflow Clarity | An explicit 8-step sequence is paired with a Done Criteria checklist, a verification step (focused tests/smoke command), and a TLS-failure feedback loop, but inline validation checkpoints between steps are mostly implied rather than explicit. | 4 / 5 |
Progressive Disclosure | The SKILL.md is a well-sectioned overview with a clearly signaled one-level-deep reference (references/capture-workflow.md) and real referenced scripts, but scripts/llm_dump.py is an unreferenced bundle file, a minor organization gap. | 4 / 5 |
Total | 17 / 20 Passed |