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

With no annotations, the description carries the full burden and it delivers a detailed trust model: it discloses an enrichment block of Meridian-derived fields, a provenance block naming derived fields with confidence bands, and explicitly states that any field not listed is the registry's own unmodified value. This directly informs the agent's reasoning about data reliability.

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 longer than average but every sentence earns its place: core row content, enrichment behavior, provenance model, usage guidance, and sibling routing are separated into clear blocks. It is front-loaded with the resource definition; the long first sentence is dense but not wasteful.

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 five-parameter tool with no output schema or annotations, the description supplies most needed output semantics: row fields, enrichment/provenance blocks, confidence bands, and filtering. It could be more complete about ordering, pagination beyond the schema, or distinction from get_recent_registrations, but the essential selection and invocation information is present.

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 80%, so the high-coverage baseline applies; page, limit, market, and status are already documented in the schema. The description only reinforces that results are filterable by market and status, while required manufacturer_id is un-described but made inferable by 'held by a manufacturer.' No additional parameter syntax or constraints are added.

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 opening clause identifies a specific resource ('Every individual registration held by a manufacturer') and enumerates the key fields returned, making the tool's scope concrete. The closing sentence names get_market_coverage as the tool for a different question, so the agent can distinguish this tool from siblings.

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 description gives an explicit when-not rule: 'Use get_market_coverage instead when the question is which markets a company is in.' It also gives usage context via filterable by market and status and actionable guidance about leaning on verbatim fields and hedging on derived ones.

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