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

Annotations only declare readOnlyHint=true, yet the description adds substantial behavioral context: the as-filed column mixes percent and bps so raw spreads must never be averaged (normalized at the store), position counts are parser-grain-dependent, unparsed BDCs return an honest-empty trend=[] rather than erroring, and caveats ride the response's tool_notes. This is well beyond what the annotation provides.

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 core purpose, then dense operational caveats; nearly every clause carries distinct information (units, grain caution, default/max, empty behavior, source). It is information-dense rather than padded, though the packing of many parenthetical asides slightly tests readability.

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?

Although no output schema exists, the description explicitly names the return shape {summary, ticker, count, spread_unit, trend} and the units, covers the empty-case behavior, the default/max for the only optional param, and the data provenance (SEC EDGAR BDC 10-Q/10-K, Oxford Ledge parse, FREE). Nothing an agent needs to call it correctly is missing.

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 coverage is 100%, so the schema already documents `ticker` and `quarters` (including the default 16 and max 24), and the description largely restates these. It adds no syntax or format detail beyond the schema, so the baseline 3 applies. Field-level semantics it adds (spread_unit in bps, priced_borrowers vs debt_positions) concern outputs, not inputs.

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+scope: a per-quarter loan-pricing trend for ONE BDC built from the parsed schedule of investments, with the exact metrics (fair-value-weighted average credit spread, average mark, position counts) and ordering (oldest-first). It names the sibling it pairs with (ol_bdc_borrower_dispersion), so an agent can distinguish it from other BDC tools without opening a schema.

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 clear actionable guidance: prefer `priced_borrowers` over `debt_positions` across quarters because position counts are parser-grain-dependent, and it pairs with ol_bdc_borrower_dispersion. It stops short of explicit when-not-to-use or routing among the broader BDC sibling set (e.g. credit_quality, mark_changes), so it's clear context without full exclusions.

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