vm-lab

Parallels macOS VM lab: GUI automation, Peekaboo, TCC, Ghostty.

Quality

75%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./skills/vm-lab/SKILL.md

Quality

Content

96%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is an efficient, highly actionable lab runbook with executable commands, real bundle references, and a strong validation workflow including feedback loops. Its only weakness is progressive disclosure: a sizeable portion of inline command/key-code reference could be split into a references file to keep SKILL.md as a leaner overview.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence — no padding about what a VM or TCC is, every section is commands and tightly-scoped guidance, and even known pitfalls are stated as terse actionable bullets. Every token earns its place.	5 / 5
Actionability	Guidance is fully executable: copy-paste-ready prlctl/sips commands, a complete guest-script heredoc pattern, concrete key codes, and a referenced helper script (scripts/parallels_type.py) that exists in the bundle. Specific examples cover the common cases (capture, TCC, typing, baseline).	5 / 5
Workflow Clarity	The skill defines a clear multi-step workflow with explicit validation: the Two-Way Validation section requires two independent signals per action, the Ghostty path sequences script-creation then launch then type, and known pitfalls give error-recovery feedback loops (clear line, shorter launcher, retry).	5 / 5
Progressive Disclosure	Structure is well-organized with clear section headers and a single one-level-deep bundle reference (scripts/parallels_type.py) that is real and correctly linked; it is not a 5 because the body is fairly long with inline command reference material that could partially live in a references/ file, leaving a minor organization gap.	4 / 5
	Total	19 / 20 Passed

Description

53%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is distinctive and uses strong domain-specific trigger terms, but it lacks any 'Use when...' trigger guidance and relies on nominal tool names rather than concrete actions, which limits completeness and specificity. Adding an explicit when-to-use clause and one or two concrete verbs would lift both.

Suggestions

Add an explicit trigger clause, e.g. 'Use when testing GUI automation, screenshot capture, or TCC prompts in a clean macOS VM.'

Replace generic labels with concrete actions, e.g. 'Automate GUI clicks/typing, capture screenshots, and validate TCC prompts inside a Parallels macOS VM.'

Consider including 'virtual machine' or 'screenshot' as synonyms to broaden natural-term coverage.

Dimension	Reasoning	Score
Specificity	The description names the domain (Parallels macOS VM lab) and lists four tools/areas (GUI automation, Peekaboo, TCC, Ghostty), but 'GUI automation' and 'TCC' are minimal/generic actions rather than concrete verbs — closer to 'Processes PDF files' than to a list of specific actions.	2 / 5
Completeness	It gives a clear 'what' (a Parallels macOS VM lab for those four areas) but contains no 'Use when...' clause or equivalent trigger guidance, which per the guidelines caps completeness at 3.	3 / 5
Trigger Term Quality	'Parallels', 'macOS VM', 'GUI automation', 'Peekaboo', 'TCC', and 'Ghostty' are the exact terms a user needing this skill would say, with good coverage; a few natural variations (e.g. 'virtual machine', 'screenshot') are missing, placing it just above the midpoint.	4 / 5
Distinctiveness Conflict Risk	The combination of 'Parallels macOS VM lab' with 'Peekaboo' and 'Ghostty' carves a clear niche with minimal overlap risk against other skills; it is mostly distinct with only minor overlap risk with generic macOS/automation skills.	4 / 5
	Total	13 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: steipete/agent-scripts
Path: skills/vm-lab/SKILL.md
Commit: dc4f583

Reviewed: 2 days ago

Table of Contents

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