langbot-env-setup

Prepare a local LangBot development and testing environment for an AI agent. Use when setting up WSL or Linux development, shared local URL variables, proxy variables, backend/frontend startup, Playwright MCP browser access, GitHub OAuth browser login, persisted Chrome profiles, or future Codex computer-use environment paths.

Quality

89%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

86%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.

A well-structured routing skill with excellent progressive disclosure and conciseness, plus an explicit completion checkpoint. The main gap is that actionable startup commands and a failure-recovery loop live only in the referenced files, not surfaced in the overview.

Suggestions

Add a minimal inline startup command or one-line example per routing branch (e.g. the actual backend/frontend start commands) so the overview is actionable without opening every reference.

Add a short feedback loop for setup failures — e.g. 'If services are not reachable, re-check proxy/URL variables in ../.env and retry startup' — to pair with the existing completion checkpoint.

Number the routing branches into an explicit sequence (start → choose browser path → start services → verify reachability) so the intended order is unambiguous rather than implied by bullet order.

Dimension	Reasoning	Score
Conciseness	Lean routing and rules body that assumes Claude's intelligence — it never explains what WSL, Playwright MCP, or OAuth are, and every line (routing bullet or rule) earns its place.	5 / 5
Actionability	Concrete, specific guidance for an instruction-only skill (explicit reference paths, "open a visible browser and let the user complete the credential steps", "reuse a fixed browser profile path"), but the executable startup detail is delegated to reference files rather than stated inline, leaving minor gaps.	4 / 5
Workflow Clarity	A clear decision-tree routing with an explicit starting point ("Always start here: read references/browser-access-selection.md") and a completion/validation checkpoint ("complete only after the target LangBot services are reachable and the browser profile can access the WebUI"), but no fix-and-retry feedback loop for setup failures.	4 / 5
Progressive Disclosure	SKILL.md is a clear overview that well-signals one-level-deep references; all seven referenced paths (browser-access-selection, service-startup, computer-use, playwright-mcp, oauth-browser-profile, wsl-notes, proxy) are real files in ./references/, and detail is appropriately split out.	5 / 5
	Total	18 / 20 Passed

Description

92%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.

A strong, third-person description that concretely enumerates the setup surface area and pairs a clear capability statement with an explicit, trigger-rich "Use when" clause. Minor room to add synonyms/extensions for maximum trigger coverage.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions ("WSL or Linux development, shared local URL variables, proxy variables, backend/frontend startup, Playwright MCP browser access, GitHub OAuth browser login, persisted Chrome profiles, ... computer-use environment paths") giving comprehensive coverage of the setup domain.	5 / 5
Completeness	Explicitly states the "what" ("Prepare a local LangBot development and testing environment for an AI agent") and a concrete "when" ("Use when setting up WSL or Linux development, ... backend/frontend startup, ...") with concrete trigger phrases.	5 / 5
Trigger Term Quality	Good keyword coverage with natural domain terms (WSL, proxy variables, Playwright MCP, GitHub OAuth, Chrome profiles, computer-use), but lacks synonyms and file extensions that would push it to a 5.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (LangBot-specific environment setup) with distinct triggers tied to a named product, giving minimal conflict risk with other skills.	5 / 5
	Total	19 / 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: langbot-app/LangBot
Path: skills/skills/langbot-env-setup/SKILL.md
Commit: 7803d56

Reviewed: about 3 hours ago

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