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livekit-agents

Build voice AI agents with LiveKit Cloud and the Agents SDK. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI", "implement handoffs", "structure agent workflows", or is working with LiveKit Agents SDK. Provides opinionated guidance for the recommended path: LiveKit Cloud + LiveKit Inference. REQUIRES writing tests for all implementations.

54

Quality

60%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/livekit-agents/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

20%

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

This skill is a verbose, largely philosophical document about voice agent development that repeatedly defers to external documentation for all concrete implementation details. It explains concepts Claude already understands (latency matters, tests are important, voice UX differs from text) while providing almost no executable code, specific commands, or copy-paste-ready examples. The heavy repetition of key rules (especially 'never trust model memory') wastes significant token budget.

Suggestions

Replace philosophical guidance with concrete, executable examples: provide a minimal working agent implementation, an actual test file using LiveKit's testing framework, and specific CLI commands for common operations.

Eliminate redundant repetition—consolidate the 'never trust model memory' rule into a single prominent callout rather than restating it 4+ times throughout the document.

Remove explanations of concepts Claude already knows (what latency is, why tests matter, how voice UX differs from text) and replace with specific, actionable patterns like code templates with placeholders.

Split into a concise SKILL.md overview (~50-80 lines) with references to supporting files for architecture principles, testing patterns, and common mistakes.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~300+ lines, with extensive repetition (the 'never trust model memory' rule is stated at least 4 times), explanations of concepts Claude already knows (what latency is, why tests matter, what voice UX constraints are), and padded sections like 'Benefits of LiveKit Inference' that add little actionable value. The summary repeats the entire document. Much of this could be cut by 60%+ without losing information.

1 / 3

Actionability

Despite its length, the skill contains almost no concrete, executable code or commands. The only code block is environment variable setup and a search query string. There are no actual agent implementation examples, no test code examples, no CLI commands, and no executable patterns. It repeatedly defers to 'consult the documentation' without providing any concrete implementation guidance itself.

1 / 3

Workflow Clarity

There are some sequenced workflows (the mandatory checklist, the test-driven development process, the fallback when MCP is unavailable), but they lack concrete validation checkpoints and executable steps. The testing workflow says 'write tests' and 'run tests' but provides no actual test code or validation commands. The overall development workflow is spread across multiple sections without a clear end-to-end sequence.

2 / 3

Progressive Disclosure

The document has clear section headers and some logical organization, but it's monolithic with no references to supporting files despite being long enough to warrant splitting. Content like architecture principles, testing strategy, and common mistakes could be separate files. There are no bundle files to reference, but the skill doesn't acknowledge this or organize itself as a concise overview pointing elsewhere.

2 / 3

Total

6

/

12

Passed

Description

100%

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

This is a strong skill description that hits all the key criteria. It provides specific actions, includes a comprehensive 'Use when...' clause with natural trigger terms, clearly identifies its technology niche (LiveKit), and adds useful scope information about the recommended path and testing requirements. Minor improvement could include mentioning file types or additional domain terms, but overall this is well-crafted.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'Build voice AI agents', 'implement handoffs', 'structure agent workflows', and specifies the technology stack (LiveKit Cloud, Agents SDK, LiveKit Inference). Also mentions writing tests as a requirement.

3 / 3

Completeness

Clearly answers both 'what' (build voice AI agents with LiveKit Cloud and Agents SDK, with opinionated guidance for recommended path) and 'when' (explicit 'Use when...' clause with multiple trigger phrases). Also includes scope constraints (requires tests).

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms users would say: 'build a voice agent', 'create a LiveKit agent', 'add voice AI', 'implement handoffs', 'structure agent workflows', 'LiveKit Agents SDK'. These are realistic phrases a user would naturally use.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a clear niche: LiveKit-specific voice AI agent development. The combination of 'LiveKit', 'voice AI agents', and 'Agents SDK' creates a very specific domain that is unlikely to conflict with other skills.

3 / 3

Total

12

/

12

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
livekit/agent-skills
Reviewed

Table of Contents

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