momentum_score

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

No annotations are provided, so the description must cover behavioral aspects. It mentions running on a separate Python service, but fails to disclose read-only nature, rate limits, data freshness, or error conditions. This leaves the agent guessing about side effects and reliability.

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 repetitive, containing the same sentence twice. It could be condensed without losing information. The example at the end is helpful but the overall structure wastes words.

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?

No output schema exists, so the description should explain the return format. It lists components (bias, confidence, etc.) but does not describe structure, field types, or how the data is presented. This is insufficient for an agent to fully understand what to expect.

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%, with clear descriptions for 'symbol' (list of assets) and 'timeframe' (optional with default). The description adds no significant extra meaning beyond the schema, so baseline 3 is appropriate.

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 provides a 'multi-asset momentum verdict' with components like bias, confidence, thesis, entry/invalidation/targets, and signal readings. It also mentions the pipeline and scoping to 10 assets, which differentiates it from siblings like 'sentiment' or 'price'.

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?

No explicit guidance on when to use this tool versus siblings. The only hint is scoping to 10 assets, but it does not explain when momentum analysis is appropriate or when alternatives like 'sentiment' might be better.

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