numeric_reasoning

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

With no annotations, the description carries the full burden. It reveals the tool checks for unit mixes, division by zero, and fact consistency, but does not disclose whether it is read-only, returns a report, mutates memory, or has side effects. It mentions memory usage but not the nature of access.

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 sentence and front-loaded with the action, but includes parenthetical academic citations (Dehaene 1997; Johnson-Laird 1983) that do not help an AI agent select or invoke the tool. These extraneous details reduce conciseness without adding operational value.

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?

The tool has a moderately specific purpose and two parameters, but no output schema or annotations. The description covers the tool's purpose and some checks but omits what the tool returns, how context_memory_ids is used, and edge-case behaviors. This is insufficient for an agent to predict tool behavior fully.

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%, so the description must compensate. It clarifies 'problem' as a Chinese math/physics problem, but does not explain 'context_memory_ids' at all. The array parameter's purpose and relationship to the tool's memory-checking behavior remain undefined.

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 performs a sanity-check on numbers and units in Chinese math/physics problems, listing specific checks (unit mixes, division by zero, consistency with known facts). This specific verb+resource scope distinguishes it from sibling tools like 'check' or 'reason'.

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 ('Sanity-check numbers and units in a Chinese math or physics problem') but does not explicitly state when to use it versus alternatives, nor does it provide exclusions or prerequisites. It gives a clear scenario but lacks explicit when-to-use or when-not-to-use guidance.

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