Reviewed competitor pricing, offer comparisons, and market-change evidence with x402 payments.
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Average 4.3/5 across 4 of 4 tools scored.
Each tool targets a distinct action: catalog discovery, single-company pricing, multi-competitor comparison, and market-level evidence brief. No overlapping purposes; descriptions make the differences explicit.
All tool names follow a consistent verb_noun pattern (compare_competitor_offers, get_company_pricing, get_exviv_catalog, get_market_evidence_brief). No mixed conventions or vague verbs.
The 4-tool set is well-scoped for a competitive intelligence service: one free catalog plus three paid data products. Each tool has a clear purpose and fits within the ideal 3-15 range.
The surface covers the full lifecycle: discover available products, get individual company data, compare multiple competitors, and receive market-wide change briefs. No obvious gaps given the paid-transaction model and x402 integration.
compare_competitor_offersCompare Reviewed Competitor OffersABuy a $1.00 USDC comparison of reviewed plans, prices, limits, features, source URLs, capture dates, and historical changes across two to four software competitors. Use for product marketing, deal support, procurement, and positioning decisions. Uses x402; the first call returns payment requirements.
| Name | Required | Description | Default |
|---|---|---|---|
| companySlugs | Yes | Two to four unique reviewed company slugs returned by get_exviv_catalog. |
| Name | Required | Description |
|---|---|---|
| intel | Yes | |
| dataset | Yes | |
| purchase | Yes | |
| productId | Yes | |
| generatedAt | Yes | |
| schemaVersion | Yes | |
| evidencePolicy | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description discloses the paid nature and flow: 'Buy a $1.00 USDC comparison' and 'Uses x402; the first call returns payment requirements.' This explains the financial side effect, which aligns with destructiveHint=true, and adds context about the payment protocol.
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: purpose, use cases, and payment behavior. It's front-loaded with the main action and no redundant 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?
With an output schema present and clear payment flow, the description covers the essential workflow: buy a comparison, provide slugs, first call gets payment requirements. It doesn't explain the output details, but that's covered by the output schema. It also doesn't mention if the comparison is cached or real-time, but that's not critical for tool 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?
The only parameter companySlugs is fully described in the schema: 'Two to four unique reviewed company slugs returned by get_exviv_catalog.' The description adds no further parameter-specific instructions, so it relies on the schema's 100% 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 states 'Buy a $1.00 USDC comparison of reviewed plans, prices, limits, features, source URLs, capture dates, and historical changes across two to four software competitors.' This clearly identifies the action (buy), resource (comparison), scope (2-4 competitors), and differentiates from siblings like get_company_pricing which focuses on a single company.
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 provides explicit use cases: 'Use for product marketing, deal support, procurement, and positioning decisions.' However, it does not mention when not to use or alternatives, so no exclusions or sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_company_pricingGet Reviewed Company PricingABuy a $0.25 USDC reviewed competitor pricing and packaging snapshot for one software company, including plans, public prices, billing terms, limits, features, source URLs, capture timestamps, and historical changes. Use for pricing research, sales battlecards, procurement, and competitive monitoring. Uses x402; the first call returns payment requirements.
| Name | Required | Description | Default |
|---|---|---|---|
| companySlug | Yes | Reviewed company slug returned by get_exviv_catalog. |
| Name | Required | Description |
|---|---|---|
| intel | Yes | |
| dataset | Yes | |
| purchase | Yes | |
| productId | Yes | |
| generatedAt | Yes | |
| schemaVersion | Yes | |
| evidencePolicy | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses critical behavioral nuances beyond the annotations: the $0.25 USDC cost, the x402 protocol, and that the first call returns payment requirements. This explains the destructiveHint=true annotation by framing it as a paid transaction, adding significant context not present in structured metadata.
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 with a distinct purpose: function, use cases, and payment details. It is front-loaded with the main action and avoids 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 output schema exists and the tool is relatively simple (one parameter), the description covers the core purpose, contents, use cases, and payment flow. It could explicitly mention the follow-up call needed after payment, but the phrase 'first call returns payment requirements' sufficiently implies the two-step process.
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% for the single parameter companySlug, which is already described as returned by get_exviv_catalog. The description does not add extra meaning about the parameter, so it neither improves nor detracts from the schema's clarity.
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 'Buy a $0.25 USDC reviewed competitor pricing and packaging snapshot for one software company' and enumerates the contents (plans, prices, billing terms, etc.). This specific verb+resource+scope distinguishes it from sibling tools like get_exviv_catalog or compare_competitor_offers.
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 use cases: 'pricing research, sales battlecards, procurement, and competitive monitoring.' However, it does not explicitly mention when to avoid this tool in favor of alternatives, nor does it name competing sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_exviv_catalogGet EXVIV Intelligence CatalogAList EXVIV competitive-intelligence products, current x402 commerce status, reviewed company inputs, markets, prices, and evidence coverage. This tool is free.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| links | Yes | |
| inputs | Yes | |
| dataset | Yes | |
| service | Yes | |
| commerce | Yes | |
| products | Yes | |
| schemaVersion | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds that the tool is "free" and shows "current" status, which provides some context beyond annotations, but it doesn't disclose response format, pagination, or potential limitations. The added value is modest.
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, with the first sentence front-loading the verb and resource, followed by a concise list of included data. The second sentence is minimal and directly useful. No filler or redundant information.
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 an output schema present and zero input parameters, the description covers the essential context: what the tool lists and that it's free. The tool's simplicity means the description is complete enough for an agent to select and invoke it 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?
The input schema has zero parameters, so the baseline is 4. The description doesn't need to explain parameters since there are none, and it doesn't add any parameter-level detail because there's nothing to add.
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" and clearly identifies the resource as "EXVIV competitive-intelligence products," further detailing the included data (x402 commerce status, inputs, markets, prices, evidence coverage). This distinguishes it from sibling tools like compare_competitor_offers or get_company_pricing, which focus on comparisons, pricing, and evidence briefs respectively.
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 when-to-use or alternatives are mentioned. The phrase "List EXVIV competitive-intelligence products" implies an overview/catalog use case, but the description does not state when to prefer this over sibling tools or mention any exclusions. It's a clear but only implied usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_market_evidence_briefGet Verified Market Evidence BriefABuy a $2.00 USDC competitive-change brief for a tracked software market: recent pricing, packaging, product, and positioning changes across monitored companies, with timestamps, classifications, commercial implications, and primary-source evidence. Use for weekly competitive monitoring and GTM planning. Uses x402; the first call returns payment requirements.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Lookback window in days. | |
| limit | No | Maximum reviewed events to return. | |
| marketSlug | Yes | Market slug returned by get_exviv_catalog. |
| Name | Required | Description |
|---|---|---|
| intel | Yes | |
| dataset | Yes | |
| purchase | Yes | |
| productId | Yes | |
| generatedAt | Yes | |
| schemaVersion | Yes | |
| evidencePolicy | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true, but the description adds valuable behavioral context: 'Uses x402; the first call returns payment requirements.' It also clarifies the $2.00 USDC cost. While it doesn't spell out the destructive side effect, the annotations cover that, and the payment flow is a useful addition 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 compact and front-loaded: the core purpose is in the first sentence, usage guidance in the second, and the payment behavior in the third. 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?
Given the output schema exists, the description doesn't need to describe return values. It covers purpose, usage, and payment behavior adequately. The only minor gap is not describing the full retry-after-payment flow, but 'first call returns payment requirements' gives enough guidance for an 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?
Schema description coverage is 100%, so the schema already documents marketSlug, days, and limit. The description does not add parameter-level detail or guidance beyond the schema, which aligns with the baseline score of 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 opens with a specific action and resource: 'Buy a $2.00 USDC competitive-change brief for a tracked software market.' It then lists concrete contents (pricing, packaging, product, positioning changes) and distinguishes itself from sibling tools like compare_competitor_offers or get_exviv_catalog by focusing on a comprehensive market-change brief.
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 states a clear use case: 'Use for weekly competitive monitoring and GTM planning.' It does not explicitly compare to alternatives or say when not to use, but the context is clear enough relative to the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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