ragbrain_discover_documents

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

No annotations are provided, so the description carries the burden. It discloses the return values (titles, headings, relevance scores) and mentions 'semantic search over summaries'. It does not discuss potential side effects, rate limits, or authentication, but the inferred read-only nature is reasonable. The description adds some behavioral context beyond the schema but could be more thorough.

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 (under 50 words) and well-structured. The key purpose is front-loaded, followed by usage guidance, example queries, and a clear link to the next step (ragbrain_search). Every sentence serves a purpose with no redundancy.

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 lack of output schema, the description adequately explains what is returned (titles, headings, relevance scores). The parameter schema is fully documented. The description also provides example queries and workflow guidance. It could mention pagination or result limits (though top_k is in schema), but overall it is complete enough for an AI agent to use 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 coverage is 100%, so baseline is 3. The description adds value by providing example queries and explaining the workflow (e.g., using the tool before searching). It also clarifies that the tool returns titles, headings, and scores, which adds meaning beyond the schema definitions. This elevates the score above baseline.

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's purpose: 'Discover documents by semantic search over their summaries.' It uses a specific verb ('Discover') and resource ('documents'), and distinguishes it from sibling tools by specifying it should be used before searching for specific content and directing to 'ragbrain_search' afterward.

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 this tool: 'Use this to find documents about a topic BEFORE searching for specific content.' It also gives example queries and names the follow-up sibling tool 'ragbrain_search'. However, it does not explicitly state when not to use it, missing full exclusion guidance.

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