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

With no annotations, the description carries the full burden, and it delivers the important access-control behavior: results are filtered by space visibility, no login is required, and unauthenticated/anonymous callers only ever see public-space data. It omits pagination/return-shape behavior for limit/offset, which is a minor gap.

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?

Four short sentences, front-loaded with the core purpose followed by scoping and auth behavior. No filler or repetition.

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?

No output schema or annotations exist, so the description must cover behavior, and it does cover the access model thoroughly. It falls slightly short by not addressing result pagination or ordering for the limit/offset parameters.

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. It explains `space` well (default empty means full search), but `q`, `limit`, and `offset` receive no semantic detail beyond their names and defaults in the schema.

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?

States a specific verb and resource: 'Full-text search over the knowledge graphs'. This implicitly separates it from siblings like brainkb_sparql (structured query) and brainkb_qa_run (QA), though it does not name them explicitly.

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?

Gives clear conditional usage for the `space` parameter ('pass to scope to one workspace, omit for a full search') and states the auth condition for anonymous callers. It stops short of explicitly routing the agent between this and sibling search/query tools.

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