Topos Preference Walk

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context: 'lattice math only; no files, no scoring' and lists the return fields of PreferenceWalkResult, which is not present in annotations or schema. No contradiction.

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 about five sentences but front-loaded with the core purpose. It is dense and includes important context without being verbose. Minor room for tightening, but overall well-structured.

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 there is no output schema, the description compensates by listing the return fields (walk, next_step, progress, etc.). It explains the tool's role in an evaluation workflow. The level of detail is sufficient for a read-only, mathematical tool with well-documented parameters.

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 description coverage is 100% with clear descriptions for each parameter (target, current, ranking). The description adds no additional parameter-level meaning beyond what the schema already provides. Baseline 3 applies.

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-noun phrase ('Turn a generator ranking into a preference-ordered relaxation walk') and clearly states it's pure/read-only lattice math. It distinguishes from sibling evaluation tools by noting it pairs with 'topos_evaluate_*' for actual metrics.

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 explicitly says when to use: 'Call after an evaluation to pick the next verdict to aim for, or to relax the goal gracefully under a token/time budget'. It also suggests pairing with evaluation tools. However, it lacks explicit contraindications or when not to use this tool versus similar siblings.

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