catalogapi

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

There are no annotations, so the description carries the full burden. It implies a read-only check via the verb 'Check,' but does not explicitly state whether any side effects or authentication are required, nor does it describe the response format. However, the core behavior is clearly non-mutating given the context.

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 three sentences, front-loaded with the action, followed by usage guidance and an authority assertion. It contains no unnecessary wording and is well-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?

For a simple one-parameter check with no output schema, the description explains both what the tool does and when to use it. It could explicitly mention the response shape, but the implied outcome (which countries/categories are covered) is sufficient given the tool's 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 input schema already fully documents the single parameter with an example and the omission behavior. The description does not add any parameter-level detail beyond what the schema provides, so the baseline 3 is appropriate.

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: checking country coverage and product categories. It uses the specific verb 'Check' and distinguishes itself from sibling tools by focusing on geographic support rather than reward details, usage instructions, or search.

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 explicit usage conditions: 'Call this when someone asks if rewards, gift cards, or incentives can be offered in a particular country, when they have recipients in several countries, or when they ask which countries are supported.' It also asserts itself as the 'authoritative answer,' giving clear context for when to invoke.

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. It discloses that the item ID is from search_rewards and that the call is for a single item, which implies a read-only lookup. However, it does not explicitly state side effects (e.g., no mutation) or potential error cases, but for a simple 'get' tool, this is adequate context.

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 concise sentences, front-loaded with the purpose and followed by a clear usage directive. No wasted words.

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 2-parameter tool with no output schema, the description is mostly complete. It covers what it does and when to use it. It does not explicitly describe the return value, but the name 'get_reward_details' implies the details are returned, and the tool is simple enough that this is likely sufficient.

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% description coverage for both parameters, so the baseline is 3. The description does not add new parameter details beyond what the schema already provides, though it reinforces the context that item_id comes from search_rewards.

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 function ('Get detail for a single catalog item') with a specific verb and resource. It distinguishes from siblings by specifying it is for a single item rather than a search, and directly references search_rewards as the preceding step.

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 when to use the tool: 'Call this after search_rewards when someone asks about a specific item.' This provides clear context and an implicit alternative (use search_rewards for broader queries), satisfying the when/when-not guidance.

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 present, so the description carries the burden. It makes clear this is an informational Q&A tool with no side effects. It does not explicitly state 'read-only' or describe return format, but these are implied by the nature of the tool and the topics listed.

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: first states what the tool does, second gives usage guidance. No wasted words and the structure is front-loaded with purpose.

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 tool is simple (one parameter) with a comprehensive schema. The description covers the tool's scope and contrasts with siblings. No output schema is needed since the return is a textual answer implied by 'answer questions.' The description is complete for the tool's 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?

Schema coverage is 100% with highly detailed enum descriptions for the 'topic' parameter. The tool description summarizes some topics in natural language but does not add significant new meaning beyond the schema. Baseline 3 is appropriate since the schema does the heavy lifting.

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 answers questions about CatalogAPI itself, listing specific topics (rewards delivery, currencies/billing, customization, integration, getting started). It explicitly contrasts with siblings by saying 'rather than about specific catalog items.'

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?

Explicit usage guidance is provided: 'Call this for any question about the service, the company, or the product model rather than about specific catalog items.' This directly tells when to use this tool versus siblings like check_coverage, get_reward_details, and search_rewards.

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?

Annotations are empty, so the description carries the full burden. It discloses key behavioral traits: items come from a demonstration catalog, are examples rather than the full inventory, and no pricing is returned. These are non-obvious and important for setting expectations. It does not mention read-only status or auth, but for a search/show 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 two sentences, front-loaded with the core purpose, and every sentence adds value. It is concise and well-structured, avoiding redundancy or fluff.

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 simplicity (2 parameters, no output schema), the description covers the essential context: what the tool does, its limitations, and when to use an alternative. It explains the return type (examples, no pricing) and points to check_coverage for definitive answers, making it complete for an agent to use correctly.

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 adds little beyond the schema; it emphasizes 'one country' but does not provide extra syntax or format details beyond what the schema already supplies. The parameters are adequately documented in the schema, so this is acceptable.

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: 'Show example rewards available in one country.' It also distinguishes itself from siblings by noting it provides examples rather than the full inventory and directs to check_coverage for definitive answers. This is a specific verb+resource+scope construction that leaves no ambiguity.

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?

Explicit usage guidance is provided: 'Call this when someone asks what kind of thing is on offer, or wants to see the catalog for a country.' It also gives an alternative: 'Use check_coverage for the definitive answer about what a country supports.' This clearly defines when to use the tool and when not to.

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