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

No annotations are provided, so the description carries the full burden. It does disclose one genuinely non-obvious behavioral trait – that it returns fixed, reviewed templates and does not execute generated code – but says nothing about the return form (text vs. file), whether it can fail, or any auth/preconditions.

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 short sentences, both of which earn their place: the first states purpose, the second states the key behavioral caveat. Front-loaded with the action and free of filler.

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?

With no output schema and no annotations, the description should clarify what is actually returned (a code string? a file? a path?) and any limits. It gestures at this ('returns fixed, reviewed templates') but leaves the return shape ambiguous, which is a meaningful gap for a generator tool.

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?

With one parameter at 100% schema description coverage ('Algorithm identifier: gcd, is_prime, or factorial'), the schema already fully documents the input. The description only restates the bounded set ('supported mathematical algorithm') without adding format or fallback semantics, so the 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?

States a specific verb and resource ('Generate a Java implementation of a supported mathematical algorithm'), and the word 'supported' signals a bounded set matching the schema's values. It does not explicitly differentiate itself from siblings like common_base_multiply or prime_analyze, but the purpose is unambiguous.

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?

There is no when-to-use guidance, no statement of when this tool is preferable to the sibling tools, and no prerequisites. The agent must infer the trigger condition entirely from the tool name and the schema's enumerated values.

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