cards

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

No annotations are provided, so the description carries the behavioral transparency burden. It clearly signals a read-only navigation operation through 'Navigate' and 'lists,' and it discloses the exact output level for each parameter combination. It does not discuss auth, rate limits, or error behavior, but those are less central for this simple listing tool.

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 entire definition is a single, front-loaded sentence with no filler. Every clause adds a concrete navigation rule, making it information-dense while remaining easy to parse.

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?

With no annotations and no output schema, the description must explain enough about expected results, and it does: each level returns sports with counts, years, products, or sets. It is slightly incomplete because it does not address invalid or mixed parameter combinations, and it does not route to sibling tools, but it is otherwise sufficient for correct invocation.

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 goes beyond the schema by defining the valid combinations of optional parameters and what each combination yields, which is meaningful semantic information the schema alone does not fully convey.

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 names a specific action ('Navigate the database hierarchy') and then explains exactly what each input combination returns. It clearly reads as an exploration/list tool rather than a search, lookup, or identify tool, so an agent can distinguish it from siblings 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 mini-navigation guide: no arguments lists sports, sport lists years, sport + year lists products, and product_id lists sets. It does not explicitly mention when not to use this tool or point to alternatives, so it misses full exclusion guidance, but the usage context is clear.

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

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

With no annotations, the description carries the behavioral transparency burden. It discloses the key trait that the result changes daily, but it does not describe what the returned data contains or whether the selection is deterministic within a day.

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 concise sentence that adds 'MyCardfolio's' and 'changes daily' beyond the title. It has no filler and front-loads the core purpose effectively.

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 zero-parameter tool this is mostly adequate, but there is no output schema and the description does not state what shape the response takes (card object, ID, name, etc.). An agent might know what to call but not what to expect back.

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 tool has zero parameters, so there is no parameter semantics for the description to add. The baseline of 4 applies because no documentation burden exists for input parameters.

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 identifies the resource ('MyCardfolio's featured card of the day') and notes that it changes daily, making its purpose reasonably clear. It doesn't use an explicit verb like 'get' or 'return', but it is distinguishable from siblings like search_cards and 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?

Usage is implied: call this tool when you want the currently featured daily card. There is no explicit guidance on when not to use it or how it relates to sibling tools such as get_card or search_cards.

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

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

With no annotations, the description carries the burden of explaining behavior, and it does so well by defining the matching logic: same year, product, card number, and subjects, but different set. It also gives a concrete example (base vs. refractor), which clarifies the intended semantics beyond the schema.

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, focused sentence with the core action front-loaded and the defining criteria placed immediately after the colon. It includes a useful example without unnecessary filler.

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 low-complexity, one-parameter tool with no output schema or annotations, the description is nearly complete: it states what the tool does, the precise variant criteria, and implies a list result. It could mention the return shape or empty-result behavior, but those are minor gaps given the simplicity.

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 single parameter card_id is already fully described in the schema ('The card_id of the card'), so schema coverage is 100%. The description adds no additional detail about the parameter's format, source, or constraints, which is acceptable given the baseline for high schema coverage.

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 uses a specific verb ('Find') and a clear resource ('parallels/variants of a card'), then precisely defines what counts as a variant by listing the matching attributes and the different-set condition. This distinguishes it from siblings like get_card or search_cards, which target a single card or broader searches.

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 clearly implies when to use the tool: when you already have a card_id and want to discover its parallels or variants. It does not explicitly name alternatives or exclusion criteria, but the context is specific enough for an agent to route correctly among the siblings.

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

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

With no annotations, the description carries the full burden of explaining behavior. It discloses the return scope: full card detail plus a few related cards from the same set. It does not describe error behavior, pagination, read-only status, or how 'related' is determined, so transparency is only partial.

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 one concise sentence that front-loads the core purpose and then adds the related-card caveat. There is no filler, no redundancy with the title or schema, and every phrase earns its place.

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, the description is mostly adequate, but there is no output schema and no detail about what 'full detail' includes. The vague notion of 'a few related cards from the same set' also leaves room for confusion with get_set_checklist or find_variants.

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 input schema already documents card_id sufficiently. The description only restates that card_id identifies the card, adding no format, example, or behavioral nuance beyond what the schema provides.

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 identifies the resource (a single card) and the lookup mechanism (by card_id), and adds a distinguishing detail: it also returns a few related cards from the same set. This separates it from broad search/browse tools, though it does not explicitly contrast with siblings like find_variants or get_set_checklist.

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 phrase 'by its card_id' implies the tool is for callers who already have a specific identifier, which is useful. However, there is no explicit guidance about when to prefer this tool over search_cards, identify_card, or get_set_checklist, so the routing decision is only implied.

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

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

With no annotations provided, the description carries the behavioral disclosure burden. It usefully discloses that the output is capped at 500 cards and that set metadata is included, which goes beyond the schema. It does not mention error cases or whether the cap truncates silently, but the key behavioral constraint is stated.

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 short sentences with no filler. The core purpose is front-loaded, and the output cap is stated as a separate concise clause that earns its place.

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 single-parameter get tool with no output schema, the description covers purpose, input, included metadata, and a critical output limit. It is concise and reasonably complete, though it could add guidance on pagination or handling sets larger than 500 cards.

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 already describes set_id with 100% coverage, so the baseline is 3. The description only repeats 'by set_id' and adds no format, validation, or default information beyond the schema.

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 identifies the resource ('checklist of cards in a set') and the input key (set_id), but it lacks an explicit verb, opening with a noun phrase rather than stating 'Retrieves' or 'Gets'. The title supplies the verb, so the tool's purpose is still unambiguous and distinct from siblings like 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 phrase 'complete checklist of cards in a set' implies this is for retrieving an entire set's card list rather than a single card or a search result, but no explicit when-to-use or alternative guidance is given. Sibling tools are named in context but the description does not direct the agent to choose this over them.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does explain the parse-and-match behavior and mentions a confidence note, giving a sense of the output. It omits details such as how many matches are returned, how confidence is expressed, and how no-match or ambiguous cases are handled.

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 one tight sentence that front-loads the action, includes an illustrative example, and states the outcome concisely. Every element earns its place with no filler.

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 single-parameter tool with no output schema, the description adequately conveys the input type and the general return behavior (best matches with confidence). It could provide more detail about match count or confidence semantics, but the essential calling contract is clear.

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 already fully documents the single parameter with a description, so the baseline is 3. The tool description adds a concrete example ('1989 Upper Deck Ken Griffey Jr #1 PSA 10'), which helps an agent understand the expected input format better than the schema alone.

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 a specific verb+resource: parse a free-text card description or eBay-style listing title and return the best database matches with a confidence note. It does not explicitly distinguish itself from siblings like search_cards or get_card, so it misses the top score.

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 the intended use case (identifying a card from natural language or a listing title) and gives an example input. However, it does not explicitly state when to use this tool over browse, search_cards, or find_variants, nor does it mention any exclusions.

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

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 that this is a full-text search over particular fields and that sport/year filters are optional, which is useful. However, it does not describe return behavior, pagination, sorting, or any other operational details beyond the basic search action.

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 compact sentences with no filler. The core operation is front-loaded, the searchable fields are listed efficiently, and the optional filters are mentioned without redundancy.

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 search tool with only one required parameter and high schema coverage, the description covers the basics adequately. However, there is no guidance about result format, limits, or how this search differs from related tools like browse and identify_card, leaving moderate gaps for an agent deciding whether to invoke it.

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 coverage is 100%, so the baseline is 3. The description adds extra semantic value by explaining that the query applies to player/subject names, card numbers, products, sets, and card details, which helps an agent craft better queries than the schema examples alone.

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 states a specific verb and resource: full-text search over the MyCardfolio sports card database. It also enumerates the searchable fields, which clarifies what the tool operates on. It does not explicitly contrast itself with siblings like browse or identify_card, but the 'full-text search' framing is specific enough to differentiate.

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 no guidance on when to use this tool versus siblings like browse, identify_card, find_variants, or get_card. It only mentions optional filters, which describes functionality rather than usage context or exclusions.

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