semantic_search

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

No annotations are provided, so the description carries the full burden. It discloses the mechanism (vector embeddings and similarity) but does not state that the operation is read-only/non-destructive, nor does it mention any limitations, rate limits, or output behavior. The safety profile is not explicitly disclosed.

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, focused sentence that directly states the tool's purpose without extraneous information. It is front-loaded and efficient.

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?

The tool has six parameters, no annotations, and no output schema, yet the description only provides the basic purpose. It lacks context on result format, default behaviors, or how this search integrates with the knowledge graph. The schema covers parameter details, but higher-level context is missing.

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 descriptions cover all six parameters with detailed explanations, so the description adds no additional parameter semantics beyond the schema. The 100% coverage supports the baseline score of 3.

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 defines the tool as a semantic search over Memento MCP entities using vector embeddings, making it distinct from the keyword-based sibling tools like search_nodes. The verb 'Search' and resource 'entities' are specific.

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 implies the tool is for semantic queries but does not explicitly state when to use it over alternatives like search_nodes, nor does it mention any exclusions or crossover conditions. Without naming sibling tools, guidance is limited to the implied semantic use case.

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