find_variantsFind parallels/variants of a card: cards sharing the same year, product, card number, and subjects but belonging to a different set (e.g. base vs. refractor).
| Name | Required | Description | Default |
|---|---|---|---|
| card_id | Yes | The card_id of the card |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral disclosure. It implies a read-only query operation and explains matching logic, but does not detail output format, pagination, error handling, or side effects. Adequate but slightly lacking in depth.
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, no wasted words. The first sentence defines the tool's purpose, the second clarifies the matching criteria. Perfectly concise and structured.
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?
Given the simple schema (one required parameter) and no output schema, the description sufficiently explains the tool's logic and selection criteria. Could be improved by mentioning the return type (list or single) or common fields, but overall complete for its complexity.
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 has 100% coverage for the single parameter card_id. The description adds meaningful context by explaining how card_id is used (to find cards sharing year, product, number, subjects), clarifying the variant logic beyond the schema's generic description.
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 finds parallels/variants of a card, specifying the matching criteria (year, product, card number, subjects) and contrasting with different set, which distinguishes it from sibling tools like get_card or search_cards.
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 provides a clear context for when to use this tool: when you need variant cards that share base attributes but differ in set. It does not explicitly mention when not to use it or provide alternative tool names, but the context is sufficient.
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.