Agentic Tools 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 adds useful context about 'advanced text matching algorithms,' 'customizable relevance scoring,' and 'quickly find relevant information,' which hints at performance and functionality. However, it doesn't disclose critical behavioral traits like whether this is a read-only operation, potential rate limits, authentication needs, or error conditions, leaving gaps for a search tool.

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 appropriately sized and front-loaded, starting with the core purpose and key features. Both sentences earn their place by adding value: the first defines the tool, and the second elaborates on use cases. It could be slightly more concise by integrating the use case into the first sentence, but overall it's efficient with zero waste.

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 tool's moderate complexity (search with 5 parameters), no annotations, and no output schema, the description is incomplete. It covers purpose and some behavioral context but lacks details on return values (e.g., result format, pagination), error handling, or performance constraints. For a search tool without structured output documentation, this leaves significant gaps for an AI agent.

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 5 parameters thoroughly. The description adds marginal value by implying the 'query' parameter uses text matching and 'threshold' relates to relevance scoring, but doesn't provide additional syntax, format details, or meaning beyond what the schema provides. Baseline 3 is appropriate when the 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's purpose with specific verbs ('search through your stored memories') and resources ('memories'), distinguishing it from siblings like 'get_memory' (single retrieval) and 'list_memories' (unfiltered listing). It specifies advanced text matching and multi-field search across titles, content, and metadata, making the purpose highly specific and differentiated.

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 clear context for when to use this tool ('perfect for retrieving past decisions, preferences, or contextual information when you need it most'), but doesn't explicitly state when not to use it or name alternatives. It implies usage for filtered searching versus 'list_memories' for unfiltered listing, but lacks explicit exclusions or named sibling comparisons.

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