athena_qhug_pareto_solve

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the solve method (local component enumeration + Pareto-pruned Minkowski convolution) and a specific guarantee (preserves every scalar-policy tie). However, it does not disclose whether the operation is read-only, mutates state, requires permissions, or has failure modes, leaving key safety/behavioral gaps.

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, tightly worded sentence that leads with the main verb 'solve' and packs the algorithm and key guarantee into 16 words. Every phrase adds distinct information, and there is no filler or tangential detail.

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?

For a complex tool with 8 parameters, no output schema, and no annotations, the description is far too brief. It does not specify what the solver returns (a solution set, a policy, etc.), what 'supported' entails, or how conflicts/dependencies are handled. The agent lacks essential context to invoke the tool correctly beyond the raw schema.

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 0%, and the description does not mention or explain any of the 8 parameters (mode, policy, patches, conflicts, etc.). The algorithm hint 'local component enumeration' loosely relates to max_component_size, but the mapping is not explicit. The self-documenting schema provides types and constraints, but the description fails to add meaningful semantics for how parameters affect the solve.

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 states a specific verb ('solve') and resource ('supported disconnected Boolean QHUG kernel'), with an algorithmic qualifier. It clearly distinguishes the tool from sibling analyzers/verifiers by focusing on exact solving rather than analysis or verification. However, the heavily specialized terminology leaves ambiguity for agents unfamiliar with the domain, preventing a top score.

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 implies usage context: it is for exactly solving a supported disconnected Boolean QHUG kernel. However, it provides no explicit when-to-use vs alternatives, no exclusions, and no mention of prerequisites or limitations. The guidance is purely implicit through the object being solved.

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