lbb_index

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

Annotations indicate it is neither read-only nor destructive, meaning it is a non-destructive mutation. The description adds that it builds/refreshes persisted indexes, but does not detail behavioral aspects like blocking behavior, the effect of the background parameter, or potential time costs. It provides some added value but not full transparency beyond annotations.

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, front-loaded sentence that conveys the core purpose without any redundant or irrelevant information. Every word is necessary.

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?

Despite the lack of an output schema, the description explains the tool's function and purpose clearly. It covers the main action and outcome. However, it does not describe what the tool returns (e.g., success status) but that is not critical given no schema. It is complete enough for an agent to understand when and why to use it.

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?

All three parameters are fully described in the input schema (100% coverage). The description does not add any extra meaning or context to the parameters, so it meets the baseline without further enhancement.

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 specifies the action (build or refresh), the resources (BM25, vector, and adjacency indexes), and the purpose (making committed facts searchable). It clearly differentiates from sibling tools like lbb_search and lbb_query, which are for querying, not building indexes.

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 should be used after committing facts to make them searchable, providing clear context. However, it lacks explicit when-not-to-use instructions or mention of alternatives among siblings, though the context is strong enough to guide the agent.

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