get_party_cohesion

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

No annotations are provided, so the description bears the full burden. It explains the Rice index calculation (excluding abstentions from denominator), handling of abstainers, and that it is a research-only tool. However, it doesn't mention idempotency or side effects, but for a read-only analysis tool this is sufficient.

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 well-structured with sections for purpose, algorithm, workflow, args, and returns. While slightly long, every part adds value. Could be slightly more concise by merging some lines, but overall efficient.

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 complexity (multiple metrics, dissenters, error handling) and the presence of an output schema, the description completely covers input, output, algorithm, and usage workflow. No gaps remain for an agent to invoke 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 0%, so the description must compensate. It fully explains bill_id (required, PRC_... format with example) and assembly (required, example '22'), adding format and context 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 it computes per-party voting cohesion for a bill, with specific metrics like Rice index, dominant position, and dissenters. It distinguishes itself from sibling tools like get_vote_results and get_member_votes by focusing on aggregate party analysis.

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 a typical workflow: use get_vote_results to get BILL_ID, then call this tool. Explicitly warns that BILL_ID (PRC_...) is required, not BILL_NO, and gives clear prerequisites.

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