Master Setter Pokémon TCG Catalog

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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently states this is a creation operation ('Create'), discloses the rate limit (1,000 requests/month), and explains how the returned key should be used (as a Bearer token). It does not mention edge cases like duplicate emails or whether the key is returned directly vs emailed, but for such a simple tool the disclosed traits are 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?

Two sentences, both densely informative, with the purpose front-loaded in the first sentence. No filler or redundant material. The description earns its place with each clause communicating an independent piece of guidance.

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 and no annotations, the description covers the essential context: what the tool does, when to use it, and how to use the result. It omits edge-case behavior (e.g., already-existing key for that email) and exact response format, but these are relatively minor for such a simple operation.

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 0%, so the description must compensate for the undocumented email parameter. The only parameter-related phrase is 'for an email address', which merely restates the parameter name and type without adding meaningful semantics. It does not explain constraints beyond the schema's format field, nor does it clarify what happens if the email is already registered. This is a clear gap.

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 action ('Create'), a specific resource ('free API key'), and the rate limit (1,000 requests/month). It distinguishes this tool from all sibling tools, which are card-related operations, by making clear this is about API key creation rather than card operations.

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 explicitly says 'Use this if you don't have a key yet', providing a clear condition for when to invoke this tool. It also tells the agent what to do with the result ('pass it as Authorization: Bearer <key>'), which effectively guides the next step. This is stronger than merely implying usage.

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?

Given that no annotations are provided, the description must carry the full burden of behavioral disclosure. It does disclose a key trait: the tool returns 'all of its printings/variants', which is valuable context. However, it does not mention error behavior, authentication requirements, or any other side effects. For a simple read operation, this is adequate but not exhaustive, so a 3 reflects the partial yet non-trivial disclosure.

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, efficient sentence with zero waste. It front-loads the core purpose ('One card by id') and immediately provides examples and scope ('all printings/variants'). Every part earns its place, and the structure is directly comprehensible.

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 getter, the description is complete: it states the purpose, gives ID format examples, and specifies what the response includes (all variants). With no output schema or annotations to rely on, this covers the essential information an agent needs to call the tool correctly. No critical details are missing.

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 provides no description for the 'id' parameter (coverage 0%). The description compensates by giving concrete examples of valid ID formats (en-base1-4, ko-sv4a-190), which clarifies the expected value and helps the agent construct a correct request. This is more than minimal compensation, hence a 4.

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 verb ('get'), resource ('card'), and scope ('by id'), and includes concrete ID examples (en-base1-4, ko-sv4a-190). It also mentions the inclusion of all printings/variants, which distinguishes it from sibling tools like search_cards or list_cards_in_set. The agent can immediately understand what this tool does and when it is the right choice.

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?

There is no explicit guidance on when to use this tool versus alternatives. While the description implies that an ID is required, it does not mention when to prefer this over search_cards (e.g., when you already have a known ID) or how it differs from list_cards_in_set. Without exclusions or named alternatives, the agent must infer usage context.

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?

No annotations are provided, so the description carries full disclosure burden. It transparently reveals an important behavioral nuance: card_count is computed from cards actually present, not stored. This goes beyond a simple 'get set' and adds value. It doesn't mention error cases or auth, but for a simple read operation that's acceptable.

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?

Exactly one sentence contains all essential information: what the tool returns, the id format example, and the notable computed property. No wasted words, perfectly 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?

For a simple get-by-id tool with one parameter and no output schema, the description is complete. It explains the id format and the key computational behavior. It doesn't describe the full return structure, but that is generally inferable and not critical for selection.

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 0%, so the description must compensate. It provides a concrete example of the id format ('ko-sv4a'), which gives meaning beyond the schema's bare string type. The description explicitly ties the only parameter to the set identification, making the parameter fully understood.

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 ('get') and resource ('set'), includes an example id format, and clearly distinguishes this from sibling tools like list_sets (which lists all sets) and get_card (which operates on cards). An agent can immediately understand what this tool does.

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 usage for fetching a single set by id, which is self-evident given the tool name and sibling context. It doesn't explicitly state when not to use it or mention alternatives, but the purpose is clear enough that an agent would not confuse it with list_sets or get_card.

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 behavioral disclosure, but it only mentions ordering and set scope. It fails to mention pagination, default limits, offset behavior, or response format, and 'every card' could misleadingly imply a single call returns the entire set.

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 with no filler, and the ordering fact plus set examples add value. Brevity is achieved, though some behavioral details are sacrificed.

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 and no annotations, so the description is the only guidance for response shape and pagination behavior. It leaves important calling details unexplained, making it insufficient for confident 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 0%, so the description must compensate. It provides useful example values for `set`, but says nothing about `limit` or `offset` beyond what the schema's types and defaults already imply.

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 operation: list every card in a set, with ordering by number. It is distinct from get_card and get_set by being set-scoped, though it doesn't explicitly contrast itself with 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?

It gives a clear context for use: retrieving all cards in a specific set, ordered by number, with concrete set-format examples. It does not explicitly say when not to use it or name alternates, but the intended scenario is evident.

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 disclosure burden, and it does add useful behavioral context: newest-first ordering and data-quality variance across languages ('14 languages; deepest coverage of...'). However, it does not disclose pagination semantics, the effect of omitting lang (the schema shows 0 required parameters), or response format. The ordering and coverage disclosures merit a 3, but the missing pagination and optional-lang behavior cap it there.

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 terse sentences deliver the core purpose first (resource, scope, ordering) followed by a useful data-coverage nuance. Every clause earns its place and there is no filler. It loses a point only because the telegraphic phrasing omits an explicit verb like 'List' and leaves the second sentence slightly cryptic.

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 listing tool the description covers the essential behavior: what is listed, for which language, and in what order. But without an output schema or annotations, it should also clarify pagination behavior (limit/offset exist in the schema) and what happens when the optional lang parameter is omitted. These gaps are notable but not fatal for a straightforward read-only enumerator.

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 only 33% (lang documented; limit/offset lack descriptions), so the description must compensate. It enriches the lang parameter with data-quality meaning (coverage depth per language), which goes beyond the schema's code-to-name mapping. However, it adds nothing about limit/offset beyond what their defaults and min/max constraints already imply, leaving about two-thirds of the parameter semantics unaddressed.

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 defines the resource precisely ('Sets (expansions, promos, decks)'), the scope ('for a language'), and the ordering ('newest first'), making the listing operation clear even though the verb is carried by the tool name. The parenthetical disambiguates domain terminology, and the resource scope distinguishes it from the get_set and list_cards_in_set siblings. It stops short of 5 because it doesn't explicitly contrast itself with those siblings or state exclusions.

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 context is inferable: to enumerate sets for a language, use this tool rather than get_set (single set) or list_cards_in_set (cards within a set). The language-coverage note ('deepest coverage of Korean, Thai, Indonesian and Chinese') hints at when results will be richest. However, no alternative tools are named and no explicit when-to-use/when-not-to-use guidance is provided, leaving selection to inference.

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 for behavioral disclosure. It mentions that names are stored in the card's own language, which is a key behavior, but it doesn't disclose other important aspects: whether multiple results can be returned, if the search is case-insensitive, or any pagination/default behavior (though the schema does provide defaults). It also doesn't mention any authentication or rate limits. That said, it does add some unique behavioral context 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 concise, two sentences, with the key filtering detail (search by localized name) front-loaded. Every sentence adds value, and there is no fluff or 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?

Given the tool's complexity (search with multiple params) and low schema coverage, the description is under-specified. It lacks information on return format (though no output schema exists), default behavior when no results found, and how 'lang' interacts with the search (e.g., is it a filter only?). Since there is no output schema, the description should clarify what the response contains, but it doesn't. Still, it covers the most crucial aspect: localized search behavior.

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 only 25%, meaning the schema documents only the 'lang' parameter explicitly. The description adds meaning for 'q' by explaining that it's a name and that it must be in the card's native language, but it doesn't elaborate on 'limit' or 'offset' semantics (which are somewhat obvious from schema defaults and bounds). The description partially compensates for the low coverage by clarifying the search term, but it doesn't fully address the undocumented 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 clearly states the tool's purpose: searching Pokémon TCG cards by name, with a specific note on language handling. It distinguishes itself from siblings like get_card (which likely fetches by ID) and list_cards_in_set (which lists cards in a set) by focusing on name-based search. The verb 'search' and resource 'cards' are specific, and the language nuance adds clarity.

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 when to use this tool: when you need to find cards by name, especially in non-English languages. It does not explicitly say when not to use it or mention alternatives, but the sibling tools are distinct enough (e.g., get_card by ID, list_cards_in_set by set) that the context is clear. The guidance on using localized names is a strong usage hint.

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