AnythingLLM MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe how it behaves: no information on permissions required, rate limits, whether it's idempotent, what the output format looks like (e.g., vector dimensions, metadata), or error conditions. For a tool that retrieves embeddings—a potentially compute-intensive operation—this lack of behavioral context is a significant gap.

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 a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple retrieval tool and front-loaded with the core action. Every word earns its place, making it easy to parse quickly.

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?

Given the complexity (retrieving embeddings likely involves computational resources) and the absence of both annotations and an output schema, the description is incomplete. It doesn't explain what 'vector embeddings' entail (e.g., model used, dimensionality), return format, or any behavioral constraints. For a tool with no structured safety or output documentation, the description should provide more context to compensate.

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?

The input schema has 100% description coverage, with clear documentation for both 'slug' and 'documentId'. The description adds no additional parameter semantics beyond what's in the schema. According to the rules, when schema_description_coverage is high (>80%), the baseline score is 3 even with no param info in the description, which applies here.

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 'Get vector embeddings for a document' clearly states the action ('Get') and resource ('vector embeddings for a document'), making the purpose immediately understandable. It distinguishes from siblings like 'embed_text' (which embeds text strings) and 'list_documents' (which lists documents), though it doesn't explicitly mention this differentiation. The description is specific but lacks explicit sibling comparison.

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. It doesn't mention prerequisites (e.g., needing a document to exist), exclusions, or comparisons to similar tools like 'embed_text' or 'search_workspace'. The agent must infer usage from the tool name and parameters alone, which is insufficient for optimal selection.

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