optimizer_match_problem

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

With no annotations, the description carries the transparency burden. It discloses that the tool does not ship implementation and returns a menu. This is useful context but does not cover all behavioral aspects like whether it's read-only or has side effects. Adequate but not excellent.

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 two sentences, front-loaded with purpose, and each sentence adds essential information. No wasted words. 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?

For a simple tool with one parameter and no output schema, the description covers key aspects: what it does, input format with examples, output purpose, and follow-up action. Completeness is high for the tool's complexity.

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% for the single parameter. The description adds examples of valid inputs (e.g., 'find a pair in an unsorted array'), which provides richer semantics than the schema alone. This exceeds the baseline 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 matches a problem description to algorithmic classes and techniques, with a specific verb 'match' and resource 'problem description'. It distinguishes from sibling tools like optimizer_get_technique which retrieves details for a known technique.

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 provides usage guidance: returns a menu to scan, and notes that implementation is not shipped (user must web search). This helps the agent understand the workflow. However, it lacks explicit when-not-to-use or alternative tool comparisons, but the context is clear enough for appropriate invocation.

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