foundation_answer_question

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

The description discloses that the tool re-runs classification and the internal model recommendation, which adds procedural context beyond the readOnlyHint/destructiveHint annotations. No contradiction is present, though it could be more explicit that no persistent changes are made.

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, direct, and front-loaded with the primary action. No filler or redundancy is present; every clause contributes meaningful information.

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 description explains the workflow (apply answer, re-run classification/recommendation) but does not state what the tool returns, especially since there is no output schema. For an agent invoking the tool, the return value or result handling is left implicit.

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 0% schema description coverage, the description must compensate for missing parameter documentation. It implies the 'answer' parameter is the user's answer, but it does not clearly explain 'analysis_id', leaving the agent to infer that it identifies the returned question/analysis.

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 uses a specific verb ('Apply') and identifies the resource ('the one returned material-reality or financial-scope question'), then states the follow-up actions. It is reasonably distinct from siblings like analyze_project or get, although it does not explicitly name alternatives or contrast with them.

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 clearly implies when to use the tool: when a single material-reality or financial-scope question has been returned and the user has provided an answer. It provides clear context but does not include exclusions or explicit alternatives among sibling tools.

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