browseNavigate the database hierarchy: no arguments lists sports with card counts; sport lists years; sport + year lists products; product_id lists sets.
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Year (requires sport), e.g. "1989" | |
| sport | No | Sport/category, e.g. "baseball" | |
| product_id | No | Product id to list its sets |
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 transparently describes the tool's context-dependent behavior (no arguments vs. sport vs. sport+year vs. product_id). It does not mention auth or rate limits, but for a read-only browsing tool, this is sufficient.
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 a single, well-structured sentence that efficiently conveys the behavior for all argument combinations. It is concise but lacks any extraneous information. A small improvement could be separating into bullet points for clarity.
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?
The description fully explains the tool's behavior for all argument combinations. Despite no output schema, the description compensates by explicitly listing what each call returns. For a hierarchical browsing tool with three optional parameters, this is complete.
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 description coverage is 100%, meaning each parameter has a description. The description adds significant context beyond the schema by explaining the hierarchical relationship and the specific output for each argument combination.
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 purpose: navigating a database hierarchy of sports, years, products, and sets. It specifies the output for different argument combinations, distinguishing it from sibling tools like search_cards or get_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 implicitly guides usage by showing how arguments change the output level. It does not explicitly state when not to use or mention alternatives, but the progression is clear. More explicit exclusions would elevate to 5.
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.
All seven tools have clearly distinct purposes: browse for hierarchy navigation, card_of_the_day for a daily feature, find_variants for parallel cards, get_card for single card detail, get_set_checklist for set checklists, identify_card for free-text parsing, and search_cards for full-text search. There is no overlap or ambiguity.
Most tool names follow a verb_noun pattern (browse, find_variants, get_card, get_set_checklist, identify_card, search_cards). The exception is card_of_the_day, which is a noun phrase, but it is a singular feature and does not disrupt overall consistency significantly.
With seven tools, the server is well-scoped for a sports card database. Each tool serves a distinct query need: navigation, search, identification, detail retrieval, and variant discovery. The count is neither too few nor too many.
The tool set covers the core read-only operations needed for a card database: browsing, searching, identifying, getting details, and listing sets. Minor gaps exist, such as lacking cross-set comparison or advanced filtering by product, but the overall surface is comprehensive for typical use.