search_nodes

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

No annotations provided, so the description carries the full burden. It discloses the hybrid search mechanism, fallback behavior, and the 6 re-ranking signals. This adds value beyond the schema, though it could mention potential limitations like pagination or performance.

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 two sentences with no waste. The first sentence front-loads the purpose, and the second adds critical behavioral details. Every word earns its place.

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 complexity (hybrid search, fallback, re-ranking) and the existence of an output schema, the description provides a solid overview. However, it omits details on pagination, maximum results, or result ordering, which would be helpful for an 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 coverage is 0%, meaning no parameter descriptions in the schema. The description only implicitly refers to the query and project via the re-ranking signals, but does not explicitly explain the parameters or their formats. The description fails to compensate for the lack of schema documentation.

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 it searches the knowledge graph using hybrid BM25 + semantic search, with a specific verb and resource, and distinguishes from sibling tools that are CRUD operations or read_graph.

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 context on when sqlite-vec is used versus fallback, and mentions re-ranking signals, but does not explicitly state when to use this tool over alternatives. However, as the only search tool among siblings, usage is implied.

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