Stock analysis

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

Adds significant value beyond annotations by disclosing rate limiting (abuse controls), Pro-only access restrictions, authentication requirements (internal_key, a2a_internal_api_key), and detailed response structure (interpretation paragraph format with specific metrics like vol_pri_angle_degree).

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?

Front-loaded with clear purpose statement. However, second paragraph is dense with implementation-specific references (analyze_std_dev, vol_pri_angle_degree) that reduce readability. Abuse control details, while useful, could be more concise.

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 the presence of an output schema, the description appropriately focuses on operational constraints (auth, rate limits) and response formatting rather than return value details. Covers the dual-mode response behavior adequately.

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?

With 0% schema description coverage, the description must document all 3 parameters but only thoroughly explains `include_interpretation`. The `limit_per_table` parameter is completely omitted, and `symbol` is only implied by 'one ticker' without explicit 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?

Opens with specific verb 'Return' and resource 'MoneyChoice aggregate stock analysis', clearly scoped to 'one ticker'. Distinct from sibling 'forecast_*' tools by focusing on aggregate analysis rather than future predictions.

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?

Provides clear guidance on when to set `include_interpretation` true (default) versus false for JSON-only output. However, lacks explicit comparison to sibling forecast tools regarding when to choose analysis over forecasting.

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