policy_question

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 not disclose whether answers are cached, whether the policy corpus is fixed or updated, whether the call has latency/cost implications from RAG retrieval, or what happens with out-of-domain questions. '(Project 3: RAG)' names a mechanism but conveys nothing actionable about behavior.

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 core sentence is front-loaded and efficient, but the 'Args:' block reads like a docstring leaking into the description and the '(Project 3: RAG)' parenthetical adds internal-context noise without agent value. Roughly half the content earns its place.

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 no-annotation tool with a 0%-coverage schema and no output schema, the description should explain the return shape (text answer? citations? confidence?) and domain boundaries. It instead borrows structure from a Python docstring, leaving the agent guessing about output and failure modes.

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, and it does list acceptable question domains (billing, cancellation, technical support, account security). That is useful scoping for the single 'question' param, but it stops short of syntax, format, or length guidance. Marginal but real value over the bare schema.

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+resource: answering a question grounded in company policy documents. The parenthetical '(Project 3: RAG)' hints at the retrieval mechanism but is cryptic internal scaffolding rather than useful differentiation. It does distinguish the tool from siblings churn_risk_score and support_ticket_category, which are classification/scoring tools rather than Q&A.

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 implicitly scopes usage by naming policy domains (billing, cancellation, technical support, account security), which tells the agent what kinds of questions belong here. However, it offers no explicit when-to-use vs alternatives guidance, no exclusion of churn_risk_score or support_ticket_category, and no prerequisites. Implied usage only.

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