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

Annotations only declare readOnlyHint=true, yet the description goes well beyond: bps normalization at the store and the warning never to average a raw spread (as-filed column mixes percent and bps), honest-empty behavior (trend=[] for an unparsed BDC), oldest-first ordering, and FREE data provenance. These are exactly the operational caveats an agent needs to interpret and trust the output.

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?

Dense but front-loaded: identity and scope come first, then unit normalization, then metric-preference guidance, then defaults and empty-state. Every clause earns its place, though the semicolon-heavy single block is slightly hard to scan.

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?

With no output schema, the description still names the return shape ({summary, ticker, count, spread_unit, trend}), the units (basis points), the empty case, and the data source/parse lineage. An agent has everything required to call it and interpret the response.

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 100%, so both parameters are already documented; the description restates the quarters default/max and clarifies ticker is one BDC but adds no format or constraint detail beyond the schema. Baseline 3 is appropriate when the schema carries the parameter burden.

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 ('per-quarter loan-pricing trend for ONE BDC') plus the exact computed fields (fair-value-weighted average credit spread, average mark, position counts) and the underlying data source (parsed schedule of investments). The 'ONE BDC' scoping and 'OLDEST-FIRST' ordering make it immediately distinguishable from siblings like ol_bdc_borrower_dispersion.

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 concrete in-tool guidance ('Prefer `priced_borrowers` over `debt_positions` across quarters: position counts are parser-grain-dependent') and names a pairing sibling (ol_bdc_borrower_dispersion). It stops short of stating when to choose this tool over an alternative tool or when not to use it.

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