Content
46%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 body chooses the right topics (action loop, sandboxing, official tool usage) and contains genuinely useful security configuration, but it is structurally damaged: three code blocks are cut off mid-line, the Sharp Edges table is broken (every row reads "Issue | <severity> | ## ..." with no actual issue text), and no step-by-step workflow with validation exists. It currently functions more as a fragmentary reference than an executable skill.
Suggestions
Complete the truncated code blocks (the pyautogui agent cut off at "scrolled {dir", the sandbox wrapper at "from dataclasses im", and the Anthropic implementation's screenshot handler) and include the missing _handle_bash/_handle_editor methods or reference files containing them.
Rebuild the Sharp Edges table: every row currently has the literal placeholder "Issue" in the issue column and a section heading pasted into the solution column, so the table conveys no actual guidance.
Move the Dockerfile, docker-compose.yml, and full implementation code into reference files (with the missing requirements.txt and supervisord.conf) and keep SKILL.md as a concise overview with one-level-deep links.
Add an ordered build-and-deploy workflow with validation checkpoints (e.g., verify the sandbox blocks network/credentials before letting the agent act), since this skill governs agents that control live computers.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Most of the body is dense, useful code and checklist content, but it includes padding Claude does not need: the basic explanation of the Perception-Reasoning-Action loop, the marketing quote "Claude Opus 4.5 is now the 'best model in the world for computer use'", and inline time-sensitive version numbers ("computer_20251124", "claude-sonnet-4-20250514") that are not isolated in a deprecated/old-patterns section. It is not a 4 because these unnecessary explanations and stale version chatter are more than minor trimming candidates. | 3 / 5 |
Actionability | There is substantial concrete guidance (pyautogui action dispatch, a Dockerfile, docker-compose with security constraints), but the code is literally truncated mid-string ("f\"scrolled {dir" and "from dataclasses im"), methods referenced are never shown (_handle_bash, _handle_editor), and the Dockerfile depends on files (requirements.txt, supervisord.conf) that are neither provided nor listed. This matches "some concrete guidance but incomplete; missing key details" rather than 4, whose code is executable with only minor gaps. | 3 / 5 |
Workflow Clarity | Sequences exist (the numbered PERCEPTION/REASONING/ACTION/FEEDBACK loop and the five isolation requirements), but there is no end-to-end workflow connecting sandbox setup to agent execution, and validation checkpoints are entirely absent — notable because this skill deploys agents that control real computers, a risky-operation context the rubric caps at 3. It is not a 2 because the pattern sequences themselves are coherent and clearly numbered, and not a 4 because there are no verify/recover steps anywhere and the error-recovery guidance (the Sharp Edges table) is broken. | 3 / 5 |
Progressive Disclosure | No bundle files exist (no references/, scripts/, or assets/ directories), and roughly 200 lines of material that clearly belongs in separate files — a full Dockerfile, a docker-compose.yml, and a long Python implementation — are inlined in SKILL.md. This matches "content that clearly belongs in separate files is inlined"; it is not a 3 because there are no references or navigation to separate material at all, and the one structure present (## Patterns headers) does not offset a monolithic body. | 2 / 5 |
Total | 11 / 20 Passed |