notebook_query

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

With no annotations provided, the description carries full weight and does so impressively: it discloses the hybrid fusion algorithm, the difference between remote (dense) and local (FTS5) processing, the privacy flag's effect, the flagging of excluded remote spaces, and the return of per-stage latency. This gives the agent a clear model of the tool's 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 efficiently front-loaded with the primary purpose, then adds a compact list of critical parameter details and return metadata. Every sentence contributes unique information, and there is no redundant filler.

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?

For a tool with no output schema, the description covers return values ('raw chunks' and 'latency_ms') and critical behavioral nuances. Given the tool's moderate complexity and the clear sibling context, the description is sufficient for an agent to select and invoke the tool correctly.

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 0%, so the description must compensate for missing parameter info. It explicitly explains the 'mode' parameter (hybrid | dense | lexical) and the 'private' parameter semantics (avoids remote dense-embedding, FTS5 still runs), which are not self-evident from the raw schema. Other parameters like notebook_id and top_k are obvious from their names and defaults.

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 a specific verb+resource: 'Hybrid search within a notebook' and details the mechanism (dense KNN + FTS5 lexical, fused with RRF). This distinguishes it from sibling tools like notebook_create or source_list, which are not search operations.

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 the tool and how to configure it (e.g., setting private=true for sensitive queries). While it does not explicitly name alternative tools or state when not to use it, the sibling tools are disparate enough that no alternative search tool exists, making the usage context sufficient.

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