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

With no annotations, the description carries the behavioral burden. It discloses that the tool fetches live market data, synthesizes it via an LLM, returns a structured narrative brief, and requires a Bearer key. It does not cover failure behavior or rate limits, but covers the most decision-relevant behaviors.

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?

Two tight sentences front-load the definition and output, then state the auth requirement. 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?

Given no output schema, the description explains the return shape well enough to know what to expect. It is complete for invocation—optional params, topic mapping, and auth are covered—but minor gaps remain around focus semantics and explicit sibling routing.

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 the baseline is 3. The description adds value by mapping the topic enum to concrete facts ('crypto' to crypto prices, 'defi' to DeFi yields, 'network' to Base block height), which is not stated in the schema. The focus parameter remains only lightly explained.

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 opens with 'Composite analyst brief' and states a specific behavior: it gathers live market facts (crypto prices, DeFi yields, Base block height) and returns an LLM-written brief. This makes the resource and output concrete and differentiates it from the single-fact sibling tools like crypto_price and base_gas.

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 'composite analyst brief' framing and mention of live market facts gives a clear context: use it when a synthesized, multi-source market brief is needed rather than a single fact. It also notes the Bearer-key prerequisite, though it does not explicitly name sibling alternatives or give when-not-to-use guidance.

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