Vibe Coding Documentation MCP (MUSE)

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions AST parsing and outputs but lacks critical details: whether analysis is read-only or has side effects, performance characteristics, rate limits, authentication requirements beyond the API key mention in schema, or what the output format looks like. The description adds some context about analysis types but leaves major behavioral aspects unspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured in two sentences that cover the core functionality and key features. Every phrase adds value: 'deep code analysis using AST parsing' establishes the method, 'extracts functions, classes, imports' specifies outputs, 'generates Mermaid diagrams' adds visualization, and 'AI-powered analysis for quality insights, security issues, and improvement suggestions' expands capabilities. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 6-parameter analysis tool with no annotations and no output schema, the description is moderately complete. It covers what the tool does and key features but lacks critical behavioral context (side effects, performance, output format) and usage guidelines. The absence of output schema means the description should ideally hint at return values, which it doesn't. It's adequate but has clear gaps for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description mentions 'AST parsing', 'Mermaid diagrams', and 'AI-powered analysis' which map to parameters but don't add significant semantic value beyond what's in the schema descriptions. It doesn't explain parameter interactions or provide usage examples. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'deep code analysis using AST parsing' and lists specific outputs (functions, classes, imports, Mermaid diagrams, AI-powered insights). It distinguishes from siblings by focusing on code analysis rather than tagging, batching, documentation generation, or session management. However, it doesn't explicitly contrast with the most similar sibling 'muse_collect_code_context'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'muse_collect_code_context' or 'muse_generate_dev_document'. It mentions AI-powered analysis requires ANTHROPIC_API_KEY in the schema but not in the description itself. There's no explicit 'when-not' or comparison with sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.