get_proxy_report

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

With no annotations, the description adequately discloses behavior: it is a read operation returning FOR/AGAINST/REFER with reasoning. It mentions configurable voting policies and presets. However, it does not explicitly state that it is non-destructive or discuss rate limits, but the 'Get' verb implies read-only.

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 a single, well-structured paragraph that front-loads the main purpose, then details analyses, policies, return format, and example usage. Every sentence adds value without redundancy.

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 explains the return format (FOR/AGAINST/REFER with severity, reasoning, data points) and mentions configurable policies, which compensates for the lack of an output schema. It is complete enough for an agent to understand inputs, outputs, and usage context.

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 each parameter (ticker, year, meeting_id). The tool description adds context like example tickers and the default for year, but does not significantly enhance the schema definitions.

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 uses a specific verb and resource: 'Get automated proxy advisory voting recommendations for a company's AGM resolutions.' It also lists the analyses performed and the return format, clearly distinguishing this tool from sibling tools like list_voting_policies or get_governance_scores.

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 explicit use cases such as 'how should I vote at [company] AGM?' and example queries like 'proxy report for AIR'. It does not specify when not to use or give alternatives, but the context is clear enough for an agent.

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