underwrite_agent_loan

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

With no annotations provided, the description carries the full load and does most of it: it discloses cost (free), auth (unauthenticated), adversarial outcome (declines about half the time), and the advisory nature of the result. It omits any note on rate limits, idempotency, or whether decisions are cached/reproducible, which leaves a modest gap for a decisioning endpoint.

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?

Front-loaded with the value proposition and cost tag, then parameter semantics, then return contract — a sensible order with little waste. The pseudo-tabular indentation in the middle is slightly awkward to parse but does not cost much.

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?

No output schema exists, and the description names the return fields (approved, credit_limit_usdc, apr_pct, tier, reason), which covers the return contract adequately. Combined with cost/auth/decline disclosures, the only material omission is the meaning and accepted format of the required `agent` identifier.

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 does well for two parameters — principal is USDC loan size, tier1_value is optional collateral in USDC, B20 tokenized stocks, or USDC on Base, with its tier/APR effect explained. But the required `agent` parameter is never defined (address? name? registry id?), which is a real invocation risk.

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 — get an underwriting decision on a loan to an AI agent — and immediately scopes it as real (advisory, not a mock). That is clearly distinguishable from sibling credit/economy tools such as get_credit_market_stats, solvscore_repgate, or get_credit_ladder, which report data rather than issue a decision.

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?

Gives real decision context: declining is common (~50%) and should be treated as a signal about the counterparty, and posting tier1_value moves the agent from reputation tier to hard tier with higher limit and lower APR. It does not name an explicit alternative tool for related credit questions (e.g. get_credit_ladder, solvscore_repgate), so the when-to-use guidance is clear but not fully routed.

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