get_agent_reputation

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the 404 response until the first score is computed, the auth requirement (agent key), the meaning of the confidence field, and the scoring basis (behavioral discipline plus repayment history). This goes well beyond a bare 'get' description. The only minor omission is an explicit statement that the operation is read-only, but the 'get' verb and the nature of the tool make that clear.

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 information-dense but every sentence earns its place: purpose, output fields, scoring logic, use case, error condition, and auth requirement. It is well-structured, starting with the core return value, then elaborating on fields, then providing context. There is zero fluff.

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?

Since there is no output schema, the description must define the return value, and it does so thoroughly: all six fields are listed, the multiplier semantics are explained with a concrete example (10000 = 1.0x), the 404 edge case is noted, and the auth requirement is stated. For a no-parameter getter with no output schema, this is as complete as one could reasonably expect.

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?

The tool has zero parameters, so the baseline is 4. The description adds contextual meaning by explaining that the tool acts on the calling agent's identity, which is the implicit parameter derived from the API key. There are no parameter semantics to explain, and the description properly acknowledges the auth key requirement.

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 ('Return') and clearly identifies the resource ('the calling agent's unified credit reputation'). It lists the exact output fields (score, band, confidence, collateralMultiplierBps, modelVersion, computedAt), which fully disambiguates it from sibling getters like get_credit_remaining or get_loan_state. This is a model of purpose clarity.

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 explicitly states the intended use case: 'Use to understand how much collateral the next borrow will require.' This gives a clear invocation context. However, it does not mention alternatives or when not to use the tool, which would be needed for a 5. Still, the guidance is helpful and actionable.

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