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

With no annotations provided, the description takes on the full transparency burden. It discloses the required Authorization header, the pass-through billing (typically under a cent), and the two-phase process (independent assessment then synthesis). This gives the agent a clear picture of what to expect.

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 two sentences long, front-loads the primary purpose, and includes only relevant details (auth, cost, process). There is no fluff or redundancy, making it efficient and easy to parse.

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 there is no output schema and the tool has a simple parameter set, the description is complete. It explains what the tool does, when to use it, the authentication requirement, the cost, and the internal workflow, leaving no critical gaps 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?

All four parameters have descriptions in the schema, so coverage is 100%. The tool description adds context about the 'diverse cost-band trio' default and clarifies the 'synthesize' control, but overall the schema already provides meaningful semantics, so the incremental gain is modest.

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 verb ('Convene'), object ('a council of DIVERSE AI models'), and purpose ('to critique a proposal or decision you are uncertain about'). It distinguishes itself from sibling tools like delegate_task by focusing on multi-model critique and synthesis.

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 explicitly says to use this when 'you are uncertain about' a proposal, providing a clear condition for use. However, it does not explicitly name alternative tools or state when not to use it, though the condition is strong enough to imply the use case.

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