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

Annotations already declare the safe read profile (readOnly, idempotent, closed-world), so the description earns credit for going further: it discloses the data lineage (CFPB HMDA 2025, actions 1,2,3, loan_type 2), the hard scope cap of 100 lenders, the 'historical observation, not a prediction' caveat, and attribution terms. It stops short of describing pagination or return ordering mechanics.

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 ANSWERS, then NOT FOR, then provenance, then attribution — a clean decision-oriented ordering with no repeated content. The licensing/attribution sentence is somewhat peripheral but justifiable for a public-data tool.

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 read-only list with no output schema, the description names the returned fields, the population (top 100 FHA lenders), and the source record, which is enough to invoke correctly. The undocumented limit parameter is the main residual gap.

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 0%, so the description must carry parameter meaning. Its quoted questions ('denies the most or the fewest', 'how wide is the spread') implicitly convey the sort dimension matching highest_denial/lowest_denial, but the parameters are never named and 'limit' is entirely unaddressed. Partial compensation only.

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 resource and scope: the ranked list of the 100 largest FHA lenders with name, slug, rate and volume, plus a concrete data point (2025 span 1.8–78.7 percent). The purpose is unmistakable, but it never names a sibling tool to differentiate from, e.g. get_lender_denial_stats, so it falls short of the 5 bar.

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?

The 'ANSWERS' block gives concrete triggering questions ('which FHA lender denies the most', 'rank FHA lenders by denial rate') and the 'NOT FOR' block explicitly excludes lenders outside the top 100 and any apply-here recommendation. Clear use context and exclusions are present, though no alternative tool is named for the excluded cases.

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