topos_preference_walk

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint. Description adds 'Pure and read-only (lattice math only; no files, no scoring)' and describes the return type's fields, providing context beyond annotations without contradicting them.

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?

Two focused sentences plus a clear bullet list of return fields. Every sentence adds value, no redundancy, and critical information is front-loaded ('Turn a generator ranking...').

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 of lattice math and preference walks, the description is complete: it explains purpose, behavior, usage context, and return value structure. No output schema exists, so describing the return fields is essential and well-handled.

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 descriptions for all parameters. The description does not add significant meaning beyond the schema for the parameters themselves, but it does describe the return type which is not covered by schema. 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?

Description clearly states 'Turn a generator ranking into a preference-ordered relaxation walk' and emphasizes it's pure and read-only. This specifies verb, resource, and scope, effectively distinguishing it from sibling tools which are about assessment, evaluation, or refactoring.

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 call: 'after an evaluation to pick the next verdict to aim for, or to relax the goal gracefully under a token/time budget.' This gives clear context and usage scenarios, though it does not explicitly exclude other uses or mention alternatives.

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