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

Beyond annotations (readOnly, idempotent, non-destructive), the description discloses meaningful behavioral traits: the selection strategy (semantic match with keyword fallback), the return shape (top panel + confidence and runner-ups), and a sensitive side-effect — the query 'may be sent to the configured embedding provider' and therefore requires authentication. This goes well beyond the annotation safety profile.

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?

Three sentences, each earning its place: the core purpose, the return/consumer information, and the auth/data-sharing caveat. The primary action is front-loaded, and there is no fluff or repetition of schema details.

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?

With a single parameter and no output schema, the description still covers the essential ground: what the tool does, what it returns (top panel, confidence, runner-ups), how the result should be consumed (run_council), and a critical behavioral caveat (external data transmission requiring auth). No obvious missing information for an agent to call it 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 100% for the single 'query' parameter, so the baseline is 3. The description adds context beyond the schema by explaining how the query is used (semantic matching, possible transmission to an embedding provider), which enriches parameter understanding beyond the bare 'The question or decision to match to a panel.'

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 states a specific verb ('Recommend'), a specific resource ('best expert panel'), and the input ('a query'), making the tool's purpose unmistakable. It also distinguishes the mechanism ('semantic match with keyword fallback') and clearly differentiates from siblings like list_panels (which lists panels) and run_council (which consumes the recommendation).

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 gives clear context for when to use the tool: 'Recommend the best expert panel for a query' and explicitly explains the downstream flow ('feed the result into run_council's panel argument'). However, it doesn't explicitly state when not to use it or name alternatives such as list_panels, so it stops short of full exclusion guidance.

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