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

Adds substantial behavioral context well beyond the readOnly/idempotent annotations: the exact scoring weights (comparables 35%, recency 20%, etc.), refusal conditions (stale comparable, book under 0.85, passive holds under $2M), size semantics ('lower bounds... never the commitment'), and the data-coverage caveat on state filtering ('about one comparable in six today'). No contradiction with annotations — the readOnly and idempotent hints are consistent with a deterministic ranked computation.

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 dense but every sentence earns its place — core ranking logic first, then scoring weights, refusal rules, caveats, and routing. It front-loads the essential mechanism before nuances and uses compact formatting (backticks, parentheticals) to pack operational detail without padding.

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 9-parameter tool with a weighted scoring model, refusal conditions, and data-quality caveats, this description is remarkably complete. It covers ranking basis, score composition, exclusions, size semantics, state-filter behavior, the geo_coverage output signal, and sibling routing. With no output schema, the only minor gap is the literal shape of the ranked list, but the scoring model makes the output predictable.

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 67% schema coverage, the description meaningfully deepens several parameters: industry is 'as the filer wrote it' with concrete example terms, states is explained as DFX-held GLEIF headquarters with a coverage caveat, and size parameters are clarified as lower bounds never the commitment. However, limit, size_max_usd, and band_max_usd receive no added meaning in either schema or description, leaving a modest residual gap.

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 states a specific verb and resource — 'Lenders ranked on the comparable facilities they CURRENTLY HOLD on BDC schedules' — and gives a concrete scenario it answers ('find lenders for a $60M unitranche for a sponsor-backed healthcare services business'). It explicitly differentiates from the sibling search_private_credit by naming it and describing the difference in industry-filter semantics.

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?

Provides explicit when-to-use guidance: 'This is the answer to... use it before search_private_credit, whose industry filter lists borrowers.' This both names the alternative and states the ordering between the two tools, leaving nothing to inference.

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