Analyst Consensus

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

Beyond annotations (readOnly, idempotent), the description discloses a critical behavioral trait: the response may not match the output schema for US accounts querying .US symbols, adding valuable context for the agent.

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 sentences with no wasted words: the first states the core function, the second addresses a critical edge case. Front-loaded and efficient.

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?

The description covers purpose, response shape inconsistency, and references the output schema. It lacks elaboration on what 'consensus estimates' includes (e.g., metrics, timeframes), but the output schema likely fills that gap.

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?

The single parameter 'symbol' is fully described in the schema. The description adds no new meaning about the parameter itself, but it does tie symbol usage to response shape, which is a behavioral nuance rather than semantic expansion.

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 it retrieves financial consensus estimates for upcoming periods. However, it does not distinguish from similar sibling tools like forecast_eps or institutional_views, so it lacks explicit differentiation.

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 for fetching consensus estimates but provides no guidance on when to use this tool versus alternatives. It notes a response shape difference for US accounts with .US symbols but does not suggest exclusions or preferred scenarios.

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