Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a tight, actionable QA workflow: concrete commands, an explicit validation-gated sequence, and well-organized self-contained sections with no padding. It exemplifies a high-quality instruction skill with no meaningful gaps.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and instruction-dense — prerequisites, instrument-selection guidance, a numbered workflow, a copy-paste skeleton, checklists, taxonomy, and a report template — with no concept-explanation padding of things Claude already knows; explanatory passages cover genuinely non-obvious gotchas (e.g., text-snapshot wide-glyph ambiguity). | 3 / 3 |
Actionability | Provides a fully executable, copy-paste-ready bash skeleton with real agent-tty subcommands and flags (doctor --json, create --json, wait --screen-stable-ms, snapshot --format text --json, record export --format webm) and disambiguates run vs type vs send-keys per step. | 3 / 3 |
Workflow Clarity | A clear 10-step sequence with explicit validation checkpoints — doctor --json prerequisites before screenshot/recording work, wait-on-observable-state instead of blind sleeps, and a destroy step — giving feedback-friendly loops for an isolated, non-destructive investigation workflow. | 3 / 3 |
Progressive Disclosure | No bundle files (references/, scripts/, assets/) exist; the skill is self-contained in a well-organized single SKILL.md with clearly labeled sections, which per the simple-skill note warrants a top score without external references. | 3 / 3 |
Total | 12 / 12 Passed |