Content
92%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is highly actionable and concise, with clearly sequenced workflows and validation/feedback checkpoints. Its one weakness is progressive disclosure: nearly everything lives inline in SKILL.md rather than being split into one-level-deep reference files.
Suggestions
Move the 'Reference: lib/browser.py' API list and 'Script conventions' into a separate references/ file (e.g. REFERENCE.md) and link to it from the body.
Consider extracting the per-mode step details (fetch, debug) into a reference doc so SKILL.md stays a concise routing overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense but almost entirely executable commands, routing tables, and tight conventions — every token earns its place and it assumes Claude's competence without explaining basics. | 3 / 3 |
Actionability | Each mode is given as copy-paste-ready bash/docker exec commands with concrete flags and inline Python, fully executable rather than pseudocode. | 3 / 3 |
Workflow Clarity | Modes are sequenced into numbered steps with an explicit pre-check validation ('docker exec agent-browser echo ok') and a run→debug feedback loop ('If failed, switch to debug mode'). | 3 / 3 |
Progressive Disclosure | Sections are well-organized and the install.sh bundle is correctly referenced, but the skill is a single monolithic file with inline reference material (lib/browser.py API, script conventions) that could be split into separate reference files. | 2 / 3 |
Total | 11 / 12 Passed |