pandamart_store_product

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

No annotations are provided, so the description carries the full burden. It does disclose a key behavior: 'Resolves the store's page slug internally,' which explains why only code and product_id are needed. It also describes the return payload's composition. However, it does not state whether the operation is read-only, what happens on invalid/not-found IDs, or any error/rate-limit behavior. For a simple get-by-id tool this is adequate but not rich.

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?

Two sentences with no filler. The first sentence states the core action; the second adds return-field details and the internal slug resolution. Every clause earns its place, and the most important information is front-loaded.

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?

There is no output schema, so the description reasonably compensates by summarizing the return fields ('same fields a shelf/search result carries plus category_id...'). It also clarifies required inputs and the optional market parameter via the schema. It does not cover not-found or error behavior, but for a single-product fetch tool the provided context is largely sufficient.

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 description coverage is 100%, so the baseline is 3. The description adds marginal value by stating 'only the darkstore code and product ID are needed,' reinforcing that market is optional and defaults to sg. It doesn't add syntax or format details beyond the schema, which already documents the origin of code and product_id fields.

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 opens with a specific verb and resource: 'Get one pandamart product's full detail.' It further clarifies the scope by contrasting with shelf/search results and naming the additional fields (category_id, per-unit pricing, nutrition). It does not explicitly name sibling tools like pandamart_store_products or pandamart_store_search, but the 'one product by ID' framing distinguishes it from list/search tools.

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?

Usage is implied rather than explicit: an agent can infer this tool is for fetching a single product's full detail when a product ID is already known. However, the description never names alternatives or states when NOT to use it (e.g., when a list of products is needed, use pandamart_store_products). With several pandamart siblings present, this is a noticeable gap.

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