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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.

69

Quality

87%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

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.

An exemplary router-style SKILL.md body: lean, condition-driven routing to a well-organized one-level-deep reference bundle, with an explicit completion checkpoint and safety rules around credentials. The main gaps are minor: a couple of routing entries lack an actionable target file, and intermediate validation/error-recovery steps are implicit rather than signposted.

DimensionReasoningScore

Conciseness

The ~25-line body is lean: a one-line purpose statement, a compact routing table, and five terse rules. It explains nothing Claude already knows and every line directs action ('read `../.env` before using URL, path, browser profile, or proxy defaults'), matching the 'every token earns its place' anchor.

5 / 5

Actionability

As an instruction-only router skill it gives concrete, specific guidance: exact file paths per condition ('read `references/browser-access-selection.md`', 'read `references/wsl-notes.md` only when running under WSL') and unambiguous directives ('Never handle the user's GitHub password, passkey, recovery code, or 2FA secret'). Not a 5 because a few entries stop short of full executability — the 'Headless-only automation' bullet names no file to act on, and 'Reuse a fixed browser profile path' leaves the actual path to be hunted down in references.

4 / 5

Workflow Clarity

The sequence is clear: shared variables first ('read `../.env` before using...'), an explicit entry point ('Always start here: read `references/browser-access-selection.md`'), conditional routing per environment, and an explicit completion checkpoint ('Treat environment setup as complete only after the target LangBot services are reachable and the browser profile can access the WebUI'). It misses the 5 anchor because per-step intermediate validation and error-recovery loops (e.g., what to check when a service fails to start) are delegated to references rather than signposted here, and the proxy fallback ('when external login... time out') is the only failure-path routing.

4 / 5

Progressive Disclosure

The body is a pure overview that splits all environment-specific detail into seven real, one-level-deep reference files, each routed with an explicit condition ('only when running under WSL', 'when external login, model provider tests, or package downloads time out'), and it even enforces the discipline in rules ('Keep environment-specific paths and commands in `references/`, not in this file'). All referenced paths verified to exist with no nested indirection.

5 / 5

Total

18

/

20

Passed

Description

83%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 description with an explicit 'Use when' clause, concrete domain-specific trigger terms, and comprehensive facet coverage. Its only weaknesses are topic-style enumeration instead of action verbs and slightly broad WSL/Linux triggers that create minor overlap risk with generic environment-setup skills.

DimensionReasoningScore

Specificity

The description names the domain ('Prepare a local LangBot development and testing environment') and enumerates several specific facets: 'backend/frontend startup, Playwright MCP browser access, GitHub OAuth browser login, persisted Chrome profiles'. It falls just short of the 5 anchor because the enumerated items are configuration areas/topics rather than multiple concrete action verbs, and a couple of edge facets (e.g., the exact nature of 'shared local URL variables') are thinly specified.

4 / 5

Completeness

It explicitly answers both parts: the 'what' ('Prepare a local LangBot development and testing environment for an AI agent') and a concrete 'when' clause ('Use when setting up WSL or Linux development, ... backend/frontend startup, Playwright MCP browser access, ...'). Both are present with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Strong natural keywords users would actually say: 'WSL', 'Linux development', 'backend/frontend startup', 'Playwright MCP', 'GitHub OAuth browser login', 'Chrome profiles', 'proxy'. Not a 5 because common phrasings like 'run/start LangBot', 'dev environment setup', or 'browser automation' variants are absent, leaving a few natural trigger terms uncovered.

4 / 5

Distinctiveness Conflict Risk

'LangBot' anchors a clear niche with tool-specific triggers (Playwright MCP, GitHub OAuth profile, LangBot services), keeping conflict risk low. It is not a 5 because the broad opening triggers 'setting up WSL or Linux development' could overlap with generic WSL/Linux environment-setup skills when LangBot is not the user's intent.

4 / 5

Total

17

/

20

Passed

Validation

100%

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
Reviewed

Table of Contents

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