deep_research_briefing

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

With no annotations, the description carries the burden of disclosure. It does mention the payment requirement (0.15 USDC on Polygon), which is a key behavioral trait not in the schema. However, it does not explain how payment works, side effects, idempotency, or error scenarios, leaving significant gaps for a tool with zero annotation coverage.

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 with no waste, front-loading the purpose and then the requirement. It is appropriately concise for the information it conveys.

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 having an output schema, the description lacks crucial context: how to supply payment (e.g., the payment_tx_hash parameter), the meaning of max_sources, and when to prefer this tool over fetching alternatives. For a tool with payment and multiple parameters, this is incomplete.

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%, and the description does not mention any parameters. It does not explain the query, max_sources, or payment_tx_hash fields, leaving the agent to rely solely on the schema, which offers minimal guidance. The description fails to compensate for the lack of parameter documentation.

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 a specific verb ('generates') and a specific resource ('multi-source AI synthesized deep research briefing'), and distinguishes itself from sibling tools that fetch raw content. An agent can tell this is a synthesis tool, not a content fetcher.

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 usage when a synthesized briefing is needed, but does not explicitly contrast it with sibling tools like fetch_clean_web_content or mention when not to use it. The payment requirement is a usage condition, but no alternatives or exclusions are stated.

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