jp-biz-opportunity

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

With no annotations, the description discloses crucial behavioral traits: each call costs 0.05 USDC, triggers an HTTP 402 payment challenge, and involves settlement mechanics. This is transparent about payment behavior, though other aspects like response on failure are omitted.

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 four sentences with front-loaded purpose. The private beta note adds context but is slightly verbose. No wasted words overall.

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 no output schema and no annotations, the description partially compensates by listing return fields (sponsor, max grant, etc.). However, it doesn't fully describe the return structure or error handling, leaving gaps for a complex paid tool.

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 covers 100% of parameters with a description. The tool description adds value by specifying that the subsidy_id comes from search_subsidies or a sample format, which aids correct parameter use.

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 it returns the full raw record of one Japanese subsidy program, listing specific fields (sponsor, max grant, etc.). It distinguishes from sibling tools like search_subsidies by focusing on a single record retrieval.

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 mentions the cost (x402 payment) and payment challenge but does not explicitly state when to use this tool versus alternatives like search_subsidies. It implies usage for detailed record access but lacks clear contextual 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 provided, so the description carries full burden. It transparently discloses that the tool returns an HTTP 402 payment challenge rather than the data directly, and explains the payment and settlement process. It also notes that the dataset unlocks for early settlers. This fully informs the agent of the unusual behavior.

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, each serving a distinct purpose: defining the resource, explaining the payment mechanism and return type, and providing a private beta note. It is front-loaded with the core purpose and efficiently adds necessary usage details 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?

Given the complexity (payment, 402 challenge, beta access), the description covers all essential aspects: what the tool returns, how it is paid for, what the agent should expect (HTTP 402), and the provisional nature of access. No output schema is provided, but the description lists the fields returned, making it complete for this tool.

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 has one parameter tender_id with a clear format description. The description adds value by listing the fields the record contains (agency, region, category, etc.), which hints at what the agent can expect from the response. Schema coverage is 100%, so the description's additional context earns above baseline.

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 tool name and title clearly indicate retrieving a tender notice record. The description specifies it returns the full raw record of a Japanese public-sector open tender notice, listing key fields (agency, region, category, publication date, submission deadline, specification summary). This clearly distinguishes it from sibling tools like search_open_tenders (search) or get_subsidy_program (subsidies).

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 explains that the tool requires payment (0.05 USDC via x402) and returns an HTTP 402 payment challenge, plus a private beta caveat about settlement and provisioning. While it does not explicitly state when not to use it versus alternatives, the sibling tool names and context (search vs. get) make the usage clear. The payment mechanism is a critical usage guideline.

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 full burden. It mentions the listing is free and that data retrieval has per-call pricing, but does not disclose rate limits, authentication needs, or behavior when no results are found.

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 'Free catalog lookup', and every word adds value. No redundancy or unnecessary details.

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 listing tool with no output schema, the description covers the dataset types and next steps, but does not specify output format, pagination, or result limits. It is adequate but leaves some gaps for a fully informed agent.

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?

There are no parameters, so the input schema is fully documented by default. The description adds value by explaining the output contains a catalog and that the api_url can be used for further retrieval, aiding the agent in understanding the tool's purpose.

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 lists Japanese public-sector business-opportunity datasets (open tender notices, subsidy programs, procurement sanction lists). It distinguishes from sibling search/get tools by being a catalog lookup, but the title and description have slight ambiguity about 'paid' vs 'free'.

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 advises using search/get tools or the returned api_url to retrieve data, implying this tool is for listing only. It provides context for when to use this tool versus siblings, but does not explicitly state when not to use or prerequisites.

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 reveals that the tool returns live data and includes attribution, implying it is a read-only operation. However, it does not disclose potential rate limits, authentication requirements, or any other behavioral traits beyond what is obvious from 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 two sentences long, front-loads the key information (FREE, live data), and contains no fluff. Every word adds value, making it highly efficient for an agent 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?

Given the tool has three parameters, no output schema, and no annotations, the description provides a reasonable overview of inputs and outputs. It mentions the data fields returned and the API source. However, it could improve by briefly hinting at the output structure or pagination behavior, but the current level is adequate for a search tool.

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 all parameters with descriptions, but the tool description adds meaning: it clarifies that keyword is required (min 2 chars) and that region is folded into the query, which is not obvious from the schema. The description also explains the deadline_within_days parameter as a submission deadline filter. However, there is a slight contradiction between the description stating keyword is required and the schema not marking it as required.

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 that the tool searches Japanese public-sector tender notices using a specific portal API, and lists the types of data returned (title, agency, region, etc.). It distinguishes itself from sibling tools like search_sanctions and search_subsidies by focusing on open tender notices.

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 mentions that keyword is required (min 2 chars) and that region is folded into the query, providing some usage context. However, it does not explicitly state when to use this tool versus alternatives like get_subsidy_program or list_opportunity_datasets, nor does it provide 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 provided, so description fully discloses payment model (0.05 USDC per call), HTTP 402 response, and beta provisioning context. This is thorough for a non-annotated 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?

Two sentences plus a beta note. Efficiently conveys purpose, payment, and special condition. Slightly verbose due to beta paragraph, but still concise.

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 1-param tool with no output schema, description explains the unique payment behavior and beta status. Lacks return format details but acceptable given 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 description coverage is 100%, so baseline 3. Description adds the Japanese term and example, but the schema already provides format and example. Minimal added value.

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?

Description clearly states the action ('look up') and resource ('suspension-of-nomination and administrative action records for one Japanese corporate number'). It is distinct from sibling tools like search_subsidies or get_tender_notice.

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?

Description specifies it is for a single corporate number and mentions payment cost, but does not explicitly differentiate from siblings or provide when-not-to-use 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 provided, so the description carries full burden. It mentions 'FREE', 'returns live data', keyword requirement with min 2 chars, and attribution. However, it does not disclose rate limits, authentication needs, or behavior on no results. Adequate but not exhaustive.

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 front-loaded key information ('FREE — returns live data'). Every phrase adds value 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?

Given 3 simple parameters and no output schema, the description covers purpose, required keyword, return fields, and data source. It lacks pagination details and usage examples, but is largely sufficient for a search tool.

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 parameter descriptions. The description adds value by stating keyword is required (schema does not have required field) and specifying min 2 chars. For industry and deadline_within_days, the description adds nothing beyond schema, so overall baseline 3.

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 searches currently-open Japanese subsidy programs by keyword, listing return fields (titles, deadlines, max amounts, target areas) and specifying the data source (jGrants API). It differentiates from sibling tools like get_subsidy_program and search_open_tenders by focus on subsidies vs tenders.

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?

No explicit guidance on when to use this tool versus alternatives (e.g., get_subsidy_program for details). The description only states what it does, not when it's appropriate or not.

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