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

With no annotations, the description carries the full burden and delivers: it discloses that no upload is needed, that data is sourced from public CFPB HMDA 2025 records with specific filters (actions 1,2,3; loan_type 2), and that this is a historical observation, not a prediction. This goes far beyond a generic list-tool description.

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 front-loads the 'ANSWERS' framing and packs only essential information: return contents, sequencing, data source, caveat, and attribution. Every clause earns its place, with no filler or redundancy.

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 zero-parameter list tool with no output schema, the description tells an agent everything needed: what is returned (size and definition), when to call it (before run_cohort), the data provenance, and the non-predictive limitation. Nothing critical 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?

There are zero parameters, so the schema imposes no semantic burden and the baseline of 4 applies. The description appropriately focuses on output and usage rather than parameter syntax, which is correct for a parameterless tool.

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 ('Returns') with a concrete resource ('public cohorts screenable without uploading anything') and explicitly states the return content ('with size and definition'). It clearly distinguishes this tool from run_cohort by positioning it as the prerequisite step, so an agent can tell them apart without opening the 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?

It provides explicit example user questions and the directive 'Call before run_cohort,' giving strong context on when to use it. However, it does not explicitly mention when not to use it or name alternatives like screen_counterparties or list_lenders, so it stops just short of full exclusionary guidance.

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