get_impact

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

No annotations are provided, so the description carries the full burden. It discloses the return fields (directional bias, confidence, driver explanation, timeframe), mentions it combines multiple sources, and notes it is free with no API key required. However, it does not explicitly state read-only behavior or any side effects, though that is implied by 'mapping' and 'returns.' The disclosure is adequate but not exhaustive.

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 efficient and front-loaded, starting with the primary purpose and then detailing return fields, filtering, and the free note. It is slightly longer than necessary but every sentence contributes useful information, and there is no fluff 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?

For a simple tool with one optional parameter and no output schema, the description is complete: it fully specifies what is returned (assets affected, bias, confidence, driver, timeframe), how to filter, and the fact that it aggregates multiple signals. An agent has enough to decide whether to call it and interpret the result, without requiring additional documentation.

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%, with the 'asset' parameter already documented with examples and omission behavior. The description adds 'Filter by specific asset to see all factors affecting it,' which is largely redundant with the schema. As coverage is high, a baseline of 3 is appropriate; the description does not add significant meaning beyond the schema.

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 specific verb 'map' and resource 'geopolitical events and crises to specific asset impacts,' and distinguishes itself from sibling tools like get_events and get_trading_signals by emphasizing asset-level impact with directional bias, confidence, and timeframe. The mention of combining multiple signals (crisis analysis, news, alpha, commodity) further differentiates its scope.

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 provides clear context for when to use the tool: to map events to asset impacts, and mentions the optional filter to focus on a specific asset. However, it does not explicitly exclude alternatives or name sibling tools, missing an opportunity to specify when not to use it (e.g., if the user only needs raw news events, get_events might be more appropriate).

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