prolog-reasoner

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 effectively describes key behaviors: it executes code and returns results, supports specific Prolog features, and implicitly handles execution (e.g., running queries). It mentions 'prevents infinite loops' via max_results in the schema, but the description could add more context on error handling or performance limits, though it's reasonably transparent overall.

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 appropriately sized and front-loaded, starting with the core purpose in the first sentence. Each subsequent sentence adds specific, valuable information about features and capabilities without redundancy, making it highly efficient and 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 the tool's moderate complexity (executing code with constraints), no annotations, and the presence of an output schema, the description is mostly complete. It covers the purpose, key features, and basic usage, but could benefit from more behavioral details like error cases or execution limits. The output schema likely handles return values, so this is adequate but not exhaustive.

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?

The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal semantic value beyond the schema, as it doesn't explain parameter interactions or provide additional usage examples. However, it implies the relationship between prolog_code and query, giving it a baseline score of 3.

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 the tool's purpose with specific verbs ('Execute Prolog code', 'Write Prolog facts and rules', 'run a query') and resources ('reasoning results'). It distinguishes itself by specifying support for CLP(FD) constraints, negation-as-failure, and SWI-Prolog features, making it highly specific and self-contained since there are no sibling tools.

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 by stating 'Write Prolog facts and rules, then run a query against them,' which provides basic context on when to use it. However, it lacks explicit guidance on when not to use it or alternatives, and there are no sibling tools to compare against, so the guidance is minimal but adequate for a standalone tool.

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