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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds real behavioral context beyond that: the output verdict vocabulary (FOR/AGAINST/REFER), that reasoning is included per resolution, and the rule taxonomy being applied.

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?

Three sentences, front-loaded with the core purpose and ending with usage guidance. The enumeration of 8 rule categories is somewhat list-heavy but does convey evaluation breadth in a compact form, so only marginal trimming is possible.

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?

With an output schema present, the description needn't explain return values, and it still previews the recommendation format. Combined with full annotation coverage and fully documented parameters, an agent has everything needed to select and call this correctly.

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% and both parameters carry examples and a default ('latest meeting'), so the schema does the heavy lifting. The description adds no additional parameter meaning (e.g. ticker format nuances or year fallback behavior), matching the baseline-3 case.

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?

Names a specific verb and resource (proxy advisory voting recommendations for AGM resolutions), and quantifies scope with 65+ rules across 8 named categories. This clearly separates it from adjacent siblings like get_agm_resolutions (raw resolutions), predict_agm_outcome (outcome probability), and get_vote_history (past votes).

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?

Explicitly states when to use it: AGM voting questions, governance concerns, or proxy advisory analysis. It gives clear positive triggers but does not name alternatives or exclusions, so it falls short of a 5 for a namespace this crowded with governance/voting siblings.

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