Enhanced Knowledge Graph Memory Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Requires embedding provider,' which adds some context about dependencies, but it doesn't describe key behaviors such as what 'similar' means in practice, how results are ordered, whether it's a read-only operation, potential rate limits, or error conditions. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 concise with two sentences that directly state the purpose and a prerequisite. It's front-loaded with the main function, and there's no wasted text. However, it could be slightly more structured by separating the prerequisite into a distinct note, but overall it's 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?

Given the complexity of a similarity search tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., read-only status, performance), output format (e.g., what data is returned), and how it differs from similar sibling tools. The prerequisite about embedding provider is helpful but insufficient for full contextual understanding.

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 parameters (entityName, limit, minSimilarity) with their types, descriptions, and defaults. The description adds no additional parameter semantics beyond what's in the schema, such as explaining 'semantic similarity' in relation to the parameters. Baseline score of 3 is appropriate as 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: 'Find entities similar to a given entity using semantic similarity.' It specifies the verb ('find'), resource ('entities'), and method ('semantic similarity'), which distinguishes it from other search tools like fuzzy_search or boolean_search. However, it doesn't explicitly differentiate from sibling tools like semantic_search or hybrid_search, which might also use semantic methods.

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 minimal usage guidance: it mentions 'Requires embedding provider,' which hints at a prerequisite but doesn't explain when to use this tool versus alternatives. There's no explicit when/when-not guidance or comparison to sibling tools like semantic_search, fuzzy_search, or hybrid_search, leaving the agent with little context for selection.

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