Agoragentic

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

Annotations provide readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds context by specifying 'stable anonymous' services and 'bounded paid resources,' which hints at reliability and scope, but doesn't detail rate limits or auth needs beyond 'accountless.' No contradiction with annotations.

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 followed by usage context. Every word contributes value, with no redundancy or fluff, making it efficient and easy 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?

With annotations covering safety and idempotency, and schema fully describing parameters, the description adds useful context like 'stable anonymous' and 'accountless buyer catalog.' However, no output schema exists, and the description doesn't explain return values or error handling, leaving gaps for a browsing 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 description coverage is 100%, with clear descriptions for 'limit,' 'include_trust,' and 'include_schemas.' The description doesn't add meaning beyond the schema, such as explaining what 'trust and settlement metadata' entails or the impact of including schemas. Baseline 3 is appropriate given high schema 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 clearly states the action ('browse') and resource ('stable anonymous x402 services'), and specifies the domain (x402.agoragentic.com). It distinguishes from siblings by mentioning 'accountless buyer catalog for bounded paid resources,' which suggests a browsing vs. transactional role, though not explicitly naming alternatives.

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 context ('accountless buyer catalog for bounded paid resources'), suggesting it's for browsing services without an account. However, it doesn't explicitly state when to use this tool versus alternatives like 'agoragentic_search' or 'agoragentic_categories,' leaving some ambiguity.

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?

The description adds valuable behavioral context beyond annotations: it explains the two-phase payment flow (unpaid attempt → payment required → paid retry), which isn't covered by annotations. Annotations provide basic hints (non-readOnly, openWorld, non-idempotent, non-destructive), but the description adds payment-specific behavior. No contradiction with annotations exists.

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 extremely concise (two sentences) and front-loaded with the core purpose. Every sentence earns its place by explaining the payment flow and retry logic without any wasted words 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?

Given the tool's complexity (payment flow, 4 parameters, no output schema), the description is reasonably complete. It explains the key behavioral pattern (payment retry) but doesn't detail error handling or response formats. With good annotations and schema coverage, it provides adequate context for an agent to use the tool 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 parameters are well-documented in the schema. The description adds minimal semantic context beyond the schema (e.g., implying 'payment_signature' is for retries), but doesn't provide significant additional meaning. Baseline 3 is appropriate given high schema 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 clearly states the specific action ('Call one stable x402 service by slug') and distinguishes it from siblings by focusing on direct service invocation rather than browsing, quoting, or other related operations. It provides a concrete example ('text-summarizer') that helps clarify the resource type.

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 states when to use this tool ('first unpaid attempt returns an x402 Payment Required payload') and when to retry ('Retry the same tool call with payment_signature to complete the paid call'). It distinguishes usage from siblings by focusing on paid service calls rather than browsing or quoting alternatives.

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 already declare readOnly, idempotent, and non-destructive traits. The description adds valuable context about what data is returned (categories plus capability counts), but does not address pagination, caching, or rate limiting 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?

Single sentence with zero waste. Front-loaded with the action verb 'List' and immediately specifies the scope (categories) and return detail (capability counts). Every word earns its place.

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 discovery tool with no parameters and safety annotations provided, the description is nearly complete. It explains the return structure adequately despite lacking an output schema. A mention of this being a prerequisite step to using the 'search' tool would achieve a 5.

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 with 100% schema coverage. Per evaluation guidelines, zero-parameter tools receive a baseline score of 4. The description appropriately does not invent parameters where none exist.

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 provides a specific verb ('List'), clear resource ('listing categories'), and distinguishes from action-oriented siblings (quote, register, search) by identifying this as a metadata/discovery tool. It further clarifies the return value includes capability counts.

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?

While the description clearly indicates this is a discovery tool, it lacks explicit guidance on when to use it versus the 'search' sibling (e.g., 'use this to discover available categories before filtering searches'). Usage is implied by the zero-parameter schema but not stated.

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 already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds value by specifying the source ('from x402.agoragentic.com') and that receipts are 'anonymous,' which are not covered by annotations. It does not contradict annotations and provides useful contextual details.

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 front-loads the core action and resource. Every word contributes to clarity without redundancy, making it appropriately sized and well-structured for quick understanding.

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 (one required parameter), rich annotations covering safety and behavior, and no output schema, the description is mostly complete. It specifies the source and anonymity, but could slightly improve by hinting at the return format or error cases, though not strictly necessary.

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%, with the parameter 'receipt_id' fully documented in the schema. The description does not add any additional meaning beyond the schema, such as format examples or edge cases, so it meets the baseline for high schema coverage without extra 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?

The description clearly states the specific action ('Fetch'), resource ('anonymous x402 edge receipt'), and key identifier ('by receipt ID'), distinguishing it from siblings like search or validation tools. It precisely defines what the tool does without being vague or tautological.

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 when you have a receipt ID from x402.agoragentic.com, but it does not explicitly state when to use this tool versus alternatives (e.g., agoragentic_search or agoragentic_validation_status) or provide exclusions. The context is clear but lacks explicit guidance on tool selection.

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 declare readOnly/idempotent/destructive hints, so the description focuses on adding behavioral context: it discloses dual return types (ranked providers vs trust snapshots/next-steps) and clarifies the routing logic. It does not contradict the read-only safety profile.

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 using parallel 'If...' structure efficiently cover both operational modes without redundancy. Every clause specifies distinct inputs and outputs, achieving high information density.

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 10 optional parameters across two distinct modes and no output schema, the description adequately compensates by detailing return values for both modes (provider rankings vs price/trust data). It successfully conveys the dual-purpose nature without requiring exhaustive parameter enumeration.

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?

With 100% schema coverage, the baseline is 3. The description adds value by mapping parameters to operational modes—implicitly grouping 'task' with constraint parameters (max_cost, max_latency_ms) and distinguishing these from listing identifiers (slug, capability_id). This semantic grouping aids correct invocation.

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 defines two distinct modes: router-aware quotes (task+constraints) vs listing-specific quotes (capability_id/listing_id/slug). It specifies distinct outputs for each (ranked providers vs price/trust snapshot), effectively distinguishing this quoting tool from sibling discovery/registration tools.

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 clear conditional logic for mode selection ('If you pass task + constraints...' vs 'If you pass capability_id...'), implicitly guiding when to use each parameter set. However, it doesn't explicitly contrast this with agoragentic_search for discovery scenarios.

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 cover key traits (read-only, idempotent, non-destructive), but the description adds valuable context: it discloses that the tool 'errors if the quoted service exceeds this price' (for max_price_usdc) and specifies return details like 'retry behavior' and 'trust metadata,' which are not captured in annotations. No contradiction with annotations exists.

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, dense sentence that front-loads the core action and efficiently lists return values. Every word contributes to understanding the tool's function without redundancy, making it highly concise and 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?

Given the tool's moderate complexity (4 parameters, no output schema) and rich annotations, the description is mostly complete. It covers purpose, key behavioral aspects, and output details. However, without an output schema, it could benefit from more explicit guidance on response structure or error handling, leaving a minor gap.

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%, providing full parameter documentation. The description does not add meaning beyond the schema (e.g., it doesn't explain slug format or trust metadata details). With high schema coverage, the baseline score of 3 is appropriate, as the description relies on the schema for parameter semantics.

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 action ('Quote one stable x402 service by slug') and specifies the resource ('stable x402 service'), distinguishing it from siblings like agoragentic_browse_services (which likely lists services) or agoragentic_call_service (which invokes a service). It provides specific output details (price, retry behavior, etc.) that further clarify its unique purpose.

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 context by specifying 'without spending,' suggesting this is a pre-call check. However, it does not explicitly state when to use this tool versus alternatives like agoragentic_quote (which may be a generic version) or agoragentic_call_service (for actual execution). Clear guidance on sibling differentiation is missing.

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?

Adds critical behavioral context beyond annotations: explicitly states the tool returns an API key and grants access to authenticated surfaces. This compensates for the missing output schema. However, it doesn't clarify the side effect of persistent agent creation or uniqueness enforcement 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?

Two sentences with zero waste: first defines the action, second defines the return value. Front-loaded with the core verb and appropriately sized for the tool's complexity.

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, the description adequately covers the return value (API key and access). Annotations provide behavioral hints. Minor gap: could mention that registration creates a persistent marketplace entity or emphasize the uniqueness constraint mentioned in the schema.

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%, documenting both agent_name and agent_type fully. The description adds no parameter-specific semantics, but none are needed given the comprehensive schema. Baseline score 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?

Specific verb 'Register' with clear resource 'agent on Agoragentic' and distinguishes clearly from operational siblings (search, quote, categories). The second sentence clarifies the deliverable (API key), cementing its purpose as the onboarding/initialization tool.

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?

Implies usage context through mention of API key returns (suggests first-step authentication), but lacks explicit 'when to use' guidance versus siblings or prerequisites. Does not state that this should be called before authenticated endpoints or warn against duplicate registrations.

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 already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds valuable domain context (supply-side marketplace, public capabilities) and workflow sequencing, but does not disclose additional behavioral traits like rate limits, response format, or pagination behavior beyond the limit parameter.

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 well-structured sentences with zero waste. The first sentence states purpose; the second provides usage context and workflow. Information is front-loaded and appropriately sized for the tool's complexity.

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 4 optional parameters and strong schema coverage, the description adequately covers the tool's purpose. It mentions the key output implication (obtaining IDs for quoting/invoking) despite the absence of an output schema, though it could briefly characterize what a 'listing' contains.

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?

Input schema has 100% description coverage with clear types and examples. The description does not add semantic clarifications beyond what the schema already provides (e.g., no guidance on query syntax or price denomination), warranting the baseline score for high-coverage schemas.

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 specific action (search) and resource (Agoragentic supply-side listings/public capabilities). It distinguishes from siblings by explicitly mentioning the workflow progression to 'quote or invoke,' which maps to agoragentic_quote and implied invocation tools in the sibling set.

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?

Provides explicit when-to-use guidance ('when you want to browse public capabilities') and outlines the multi-step workflow (browse → quote/invoke). It implicitly signals that this tool is for discovery, not execution, though it could more explicitly state when to skip this step (e.g., 'if you already know the listing ID').

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 already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, covering safety and idempotency. The description adds valuable context by specifying that this tool does not invoke paid services, which is not covered by annotations. However, it does not mention potential rate limits, authentication needs, or detailed behavioral traits like pagination or error handling, keeping it from a perfect score.

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, well-structured sentence that front-loads the purpose ('List...') and efficiently includes key usage guidance ('without invoking a paid service'). There is no wasted text, and every part of the sentence adds value, making it highly concise and effective.

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 (listing multiple status aspects), annotations provide good coverage (read-only, non-destructive, idempotent), and schema coverage is 100%. The description adds context about avoiding paid services, which is helpful. However, without an output schema, it does not explain return values or format, leaving a minor gap in completeness for a status-listing 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 1 parameter with 100% description coverage, documenting 'include_inactive' with its type, default, and description. The description does not add any parameter-specific information beyond what the schema provides, such as explaining the implications of including inactive verifiers. With high schema coverage, the baseline is 3, and the description does not compensate with additional semantics.

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 specific verb 'List' and enumerates the resources: 'Agoragentic execution verifiers, pre-execution arbiter posture, lifecycle states, and Nava opt-in readiness'. It distinguishes from siblings by specifying this is for status listing without invoking paid services, unlike tools like 'agoragentic_quote' or 'agoragentic_register' which likely involve transactions or registrations.

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 states when to use this tool: to get validation status information 'without invoking a paid service'. This provides clear guidance to use this for free status checks versus paid alternatives, and it implicitly suggests alternatives like paid services for more detailed actions, helping differentiate from siblings like 'agoragentic_quote' or 'agoragentic_register'.

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?

While annotations indicate idempotentHint=true and readOnlyHint=false, the description adds crucial behavioral context about the specific stateful handshake (402 challenge response flow) and what happens on invocation (returns challenge until signature supplied). It does not contradict annotations and explains the 'free' nature of the test.

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 consists of two highly efficient sentences. The first establishes purpose and cost model; the second discloses the critical behavioral contract (challenge/response). No words are wasted, and the information is front-loaded effectively.

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 this is a simple test utility with two optional parameters, no output schema, and clear annotations (non-destructive, idempotent), the description adequately covers the testing purpose and protocol behavior. It could be improved by briefly describing the success state or return value, but it is sufficient 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?

With 100% schema description coverage, the schema already fully documents both parameters. The description adds minimal semantic value regarding parameters themselves, though it conceptually references the 'retry' flow matching the payment_signature parameter. Baseline 3 is appropriate when schema coverage is complete.

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 precisely states the tool tests the 'x402 402->sign->retry pipeline' specifically against Agoragentic, distinguishing it from sibling tools (categories, quote, register, search) by focusing on the payment protocol testing domain. It includes the specific verb (test) and clarifies the 'free' scope ('without spending real USDC').

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 appropriate usage context (testing/development via 'without spending real USDC') and explains the two-step invocation pattern ('Returns the PAYMENT-REQUIRED challenge until you retry'). However, it lacks explicit guidance on when to use production alternatives (e.g., agoragentic_quote) instead of this test utility.

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