search_nodes

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 that matching is case-insensitive substring across specific fields (names, types, observation content). This gives good behavioral insight, though it does not explicitly state that the operation is read-only.

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. The first sentence clearly states the action and resource, and the second adds matching criteria. No extraneous content.

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 simplicity (one parameter, many siblings) and lack of output schema, the description is fairly complete. It covers purpose, matching behavior, and implicitly contrasts with search_nodes_semantic. Minor gap: it does not describe the return format, but this is acceptable given no output schema.

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%, establishing a baseline of 3. The description adds significant value by specifying that the query matches against entity names, types, and observation content using case-insensitive substring match, details beyond the schema's parameter description.

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 searches for nodes in the knowledge graph using a text query, matching against entity names, types, and observation content. It distinguishes from the sibling search_nodes_semantic by specifying case-insensitive substring match, implying the sibling uses different semantics.

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 on when to use the tool (text-based substring matching) and implicitly distinguishes from the semantic search sibling. However, it does not explicitly state when not to use it or list alternative tools beyond the implied contrast.

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