How a store is coded

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

With no annotations provided, the description carries the behavioral burden. It does disclose useful context: the data is 'as RightCard's directory files it' and uses 'the same ranking the app uses,' plus a caveat about stores like Walmart/Target and Costco/Sam's. However, it does not describe matching behavior, response shape, or failure handling.

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 concise and front-loaded with the core output fields. The caveat and examples are useful and add clarity without bloat. The title is somewhat redundant but does not harm the overall structure.

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 simple one-parameter lookup with no output schema or annotations, the description covers the main return data and an important edge-case caveat. However, it omits practical invocation details such as how the store name should be provided, whether matching is exact or fuzzy, and what happens for unknown stores. This leaves an agent with some reasonable but not fully certain ground.

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?

The input schema has one parameter, 'name', with 0% description coverage, so the description must compensate. It implies the input is a store name by saying 'The store's...' and giving examples like Walmart/Target, but it never explicitly says 'pass the store name' or describes acceptable formats. This is only partial compensation for the missing schema documentation.

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 clearly states what information the tool provides: the store's reward category, merchant type, and merchant-code caveat. It is not a tautology and the resource (store merchant coding) is evident. However, it does not explicitly differentiate itself from sibling tools like search_cards or best_card.

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 implies that the tool is used to look up a store's coding details, but it gives no explicit guidance on when to choose this tool over alternatives. There is no mention of exclusions, prerequisites, or comparison with sibling tools. The agent must infer usage entirely from the tool name and title.

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