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get_npip_stock_codes

Read-onlyIdempotent

Resolve biological poultry and game-bird varieties to regulatory federal NPIP stock numbers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional pagination limit (default 50, max 200)
queryNoOptional keyword search for variety name or code.
cursorNoOptional pagination cursor
categoryNoOptional filter: game-birds, waterfowl, or commercial.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered without the description. The description contributes the fact that this is a lookup/mapping operation against a federal regulatory dataset, but adds nothing about result shape, result size, or how partial matches behave.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler. The verb and the mapping are stated in the first few words, which is exactly the right shape for a short lookup tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a parameterless-required, read-only lookup with a fully documented input schema and no output schema, the description covers what an agent needs to decide to call it. It could be marginally stronger by signaling that results are a code mapping rather than a full variety record, but nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so limit, query, cursor and category are all documented in the schema itself. The description adds no extra semantics such as which category values pair with which variety types, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb ('Resolve') plus a clear resource ('biological poultry and game-bird varieties') and target ('regulatory federal NPIP stock numbers'). It implies the tool maps varieties to regulatory codes rather than enumerating them, which distinguishes it from the nearby list_quail_varieties, though it never names that sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no statement of when to reach for this tool versus list_quail_varieties or the other bird-related lookups, and no prerequisites or exclusions are mentioned. The agent must infer applicability from the purpose sentence alone.

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

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