get_productGet one Agent Rails product by id/ASIN. Prefer over opening retailer pages in a browser. Show item.buy to the human.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | Product id or ASIN |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is known. The description adds useful behavioral context by instructing the agent to 'Show item.buy to the human,' clarifying how the result should be surfaced. It also notes a preference over browser navigation, which is an additional behavioral trait. No contradictions with annotations.
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 two sentences, with the core purpose stated first and the usage guidance second. Every sentence earns its place: no fluff, no repetition, clear and front-loaded. This is a model of concise, well-structured documentation.
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 tool with a single parameter, clear annotations, and no output schema, the description is complete. It explains what the tool does, when to use it, and what to do with the output. The sibling context (search_products, compare_products) reinforces that this is the point-retrieval tool, and the description covers all necessary aspects for correct usage.
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 schema provides 100% coverage for the single parameter, product_id, with the description 'Product id or ASIN.' The tool description echoes this by saying 'by id/ASIN,' but adds no new semantic information beyond the schema. The baseline of 3 is appropriate since the schema already explains the parameter fully.
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 the tool's function: 'Get one Agent Rails product by id/ASIN.' It uses a specific verb and resource, and the phrase 'one product' distinguishes it from sibling tools like search_products, which would return multiple results. The additional context about showing item.buy further clarifies its role.
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 explicit usage guidance: 'Prefer over opening retailer pages in a browser.' This tells the agent when to choose this tool over a less efficient alternative. It also implies that this tool is for retrieving a specific product by ID/ASIN. While it doesn't explicitly name sibling alternatives, the context is clear enough for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct action: capability check, search, single product retrieval, comparison, and link conversion. Descriptions explicitly cross-reference when to use each (e.g., 'if web search found ASINs, call make_buy_link'), eliminating overlap.
Most tools follow a clear verb_noun pattern (search_products, get_product, compare_products, make_buy_link). The exception is agent_rails_manifest, which is a meta-tool named after the server, deviating from the verb-first convention.
Five tools is well-scoped for a shopping assistant: the core operations of searching, retrieving, comparing, and converting to buy links are each represented. No redundant or unnecessary tools inflate the set.
The tool set covers the full shopping workflow from discovery (search_products) to purchase link generation (make_buy_link), including single product lookup and comparison. The manifest ensures agents can quickly understand when the server should be used, filling an orientation gap.