AgentDataHub Gateway

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 discloses useful behavioral details like pricing per tier ($0.001 chat, $0.04 image/reasoning), free trial via wallet, and auto-tiering. However, it omits other behavioral traits such as potential privacy concerns, rate limits, or what happens when the prompt is ambiguous, leaving some ambiguity.

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 and front-loaded, with the main purpose stated first. It efficiently communicates tiering and usage in a few sentences. However, it includes promotional text ('Grand Opening 8折') that is not operationally useful, and the last sentence 'Auto-switches by task type' is slightly redundant with the first sentence, costing a point.

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 covers purpose, usage, pricing, and the free trial mechanism. It does not explicitly describe return values, but the tier types (chat/image/reasoning) make the output nature clear. Missing details like error handling or authentication are not critical 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?

Schema coverage is 100% for the two parameters (prompt, wallet), so the baseline is 3. The description adds meaningful context beyond the schema by explaining that the prompt type determines the tier and price, and that wallet is optional for the free trial. This enriches understanding of how the parameters influence behavior.

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 tool as a unified AI gateway that auto-tiers requests into chat, image generation, and deep reasoning. It states the scope and behavior ('auto-tiers', 'auto-switches by task type'), and the sibling tools (fetch_data, get_product_info, list_products) are unrelated, making this tool's distinct purpose evident.

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 usage instructions ('Pass prompt; wallet optional for free trial') but does not explicitly state when to use this tool versus alternatives. Since sibling tools are unrelated, there is no direct alternative, but the lack of explicit 'when' or 'when-not' guidance leaves the context implied rather than fully explicit.

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. It discloses a key behavioral trait: without payment, an x402 402 payment challenge is returned, and passing a wallet enables free trial/paid access. This goes beyond the schema and helps the agent anticipate the payment flow. It does not mention side effects, but 'fetch' implies a read operation.

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 that front-loads the main purpose and then explains the payment nuance. Every word earns its place with no 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?

With no output schema, the description should clarify return behavior. It implicitly suggests that with payment the data product is returned, and without payment a 402 challenge is returned, but it does not explicitly describe the success response or mention alternative error cases. It also lacks comparison to sibling tools, making it only moderately 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 covers only the wallet parameter with a description, while id lacks any description (50% coverage). The description adds context for wallet (free trial/paid access) and the consequence of omitting it, but does not explain what 'id' refers to. Since id is critical, the description only partially compensates for the schema 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 the tool's function: 'Fetch a data product.' The verb 'fetch' and resource 'data product' are specific, and the payment context distinguishes it from siblings like list_products and get_product_info, which likely handle listing and metadata.

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 instructions on how to invoke the tool (passing wallet for free trial/paid access, or expect a 402 challenge) but does not explicitly compare to sibling tools or state when to choose this over alternatives. Usage is implied rather than clearly differentiated.

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 mentions 'Free' and 'payment instructions' but does not disclose error behavior, authentication requirements, rate limits, or the exact structure of the returned data. This is a bare minimum for a read operation without safety hints.

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, front-loaded sentence that clearly states the action and key details. It contains no filler or redundant information, making it appropriately concise for a simple parameterized get-by-id tool.

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 with one required parameter and no output schema, so the description's mention of 'details and payment instructions' gives a general sense of the return. However, it does not clarify what 'details' entails, potential failure modes, or that a valid ID might need to come from list_products, leaving some gaps for an agent to handle.

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 describes the 'id' parameter with an example ('econ-fred'). The description adds only that the tool works 'by id', which aligns with the schema but does not provide additional syntax, format, or constraints beyond what the schema already offers. With 100% schema coverage, the baseline of 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 retrieves details and payment instructions for a single product by its ID, using the verb 'Get' and identifying the resource. It distinguishes itself from siblings like list_products by specifying 'one product by id' rather than listing all products.

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 'for one product by id' implies this tool is for fetching a specific product's details, as opposed to listing products. However, it does not explicitly mention when not to use it or point to alternatives like list_products, so the usage guidance remains implicit rather than explicit.

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 the burden. It discloses that the tool is free and indicates the returned fields (id, price USD, description), which is useful. However, it does not mention any other behavioral aspects like pagination, response format, or rate limits, though for a simple list tool this may be 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?

The description is a single, efficient sentence that clearly states the function, scope, output fields, and cost. Every part contributes value, and the key information is 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, zero-parameter listing tool with no output schema and no annotations, the description provides sufficient context: what is listed, where it is from, the fields returned, and that it is free. It could mention response format or pagination, but those are not essential for a basic list 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?

The tool has zero parameters, so the baseline is 4. The description does not need to elaborate on any parameter semantics since there are none; it correctly focuses on the tool's output and cost.

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 ('List all') and names the exact resource ('pay-per-call data products on AgentDatum'), making the tool's function unmistakable. It also implies differentiation from sibling tools like get_product_info, which likely targets a single product.

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 the tool (for obtaining a full list of products) but does not explicitly contrast it with alternatives such as get_product_info or fetch_data. There is no 'when not to use' guidance, so the usage context is only inferred.

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