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

With no annotations provided, the description carries the full burden and does well by disclosing critical behavioral traits: it's a payment-committing action ('This commits the payment'), describes fund flow ('funds go to escrow until delivery is verified'), and mentions authentication requirements ('Requires API key'). It doesn't cover rate limits or error conditions, but provides substantial operational 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 perfectly concise with three information-dense sentences that each earn their place: first states the core action, second explains the commitment and escrow mechanics, third specifies authentication. No wasted words, front-loaded with the primary 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?

For a payment-committing tool with no annotations and no output schema, the description does well by explaining the financial commitment, escrow mechanism, and authentication. It could be more complete by mentioning what happens after acceptance (e.g., thread status changes) or potential errors, but covers the essential transactional context adequately.

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% (the single parameter 'thread_id' is fully documented in the schema), so the baseline is 3. The description doesn't add any parameter-specific information beyond what the schema already provides about the thread_id parameter.

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 ('accepts a provider's price proposal and pays from pre-funded balance') and distinguishes it from siblings like 'propose_price' (which creates proposals) and 'decline_thread' (which rejects them). It specifies the exact resource being acted upon (a price proposal in a thread).

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 context for when to use this tool ('accepts a provider's price proposal') and mentions a prerequisite ('Requires API key'), but doesn't explicitly state when NOT to use it or name specific alternatives like 'decline_thread' for rejecting proposals. It implies usage when a proposal is pending in a thread.

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 states the tool is for viewing history (implying read-only) and mentions an API key requirement, but lacks details on authentication specifics, rate limits, pagination behavior (beyond schema parameters), error handling, or data freshness. For a tool with no annotation coverage, this leaves significant gaps in understanding its operational traits.

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 two sentences that directly state the purpose and a key requirement. There's no wasted language or redundancy. However, it could be slightly more structured by separating the purpose from prerequisites for better readability, but it remains efficient 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 the tool's moderate complexity (viewing transaction history with pagination), no annotations, no output schema, and 100% schema coverage, the description is minimally adequate. It covers the core purpose and authentication need but lacks details on output format, error cases, or behavioral nuances. For a tool with no output schema, more information on return values would be beneficial, but it meets basic requirements.

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 description adds no parameter-specific information beyond what's in the input schema, which has 100% coverage with clear descriptions for 'limit' and 'offset'. The baseline score of 3 is appropriate because the schema adequately documents the parameters, and the description doesn't need to compensate for any gaps. However, it also doesn't enhance understanding of how these parameters affect the transaction history view.

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 purpose: 'View your balance transaction history on the402.ai. Shows deposits, purchases, refunds, and other balance changes.' It specifies the verb ('view') and resource ('balance transaction history'), and lists the types of transactions included. However, it doesn't explicitly differentiate from sibling tools like 'check_balance' or 'list_purchases', which might have overlapping functionality.

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 minimal usage guidance. It mentions 'Requires API key' as a prerequisite, but offers no explicit advice on when to use this tool versus alternatives like 'check_balance' or 'list_purchases'. There's no context on when this tool is preferred or what scenarios it's designed for, leaving the agent to infer usage from the purpose alone.

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 adds valuable context beyond basic functionality: it specifies the catalog scope ('on the402.ai'), types of goods sold ('by providers'), and authentication requirements ('No authentication required'). However, it does not mention rate limits, pagination behavior, or error handling, leaving some gaps.

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 appropriately sized and front-loaded, with three concise sentences that each earn their place: the first states the core purpose, the second elaborates on content and scope, and the third covers search support and authentication. There is zero waste or 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 tool's moderate complexity (search functionality with 3 parameters), no annotations, and no output schema, the description is fairly complete. It covers purpose, scope, content types, search support, and authentication, but lacks details on return values, error cases, or pagination behavior, which would be helpful for an agent to use it effectively.

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 all parameters (query, limit, offset) with descriptions. The description adds marginal value by implying keyword search functionality ('Supports keyword search'), but does not provide additional syntax, format details, or constraints beyond what the schema specifies. Baseline 3 is appropriate as 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's purpose with specific verb ('Search') and resource ('digital product catalog on the402.ai'), and distinguishes it from siblings by specifying the types of content (downloadable files, datasets, templates, digital goods) and the catalog scope. It avoids tautology by providing details beyond the name 'browse_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 description provides clear context for when to use this tool ('Search the digital product catalog... Supports keyword search'), but does not explicitly state when not to use it or name alternatives. It implies usage for catalog searches without specifying prerequisites like authentication (stated as 'No authentication required'), but lacks explicit exclusions or sibling comparisons.

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 full burden for behavioral disclosure. It effectively communicates key behavioral traits: this is a read operation (implied by 'check'), it requires authentication ('Requires API key'), and it's specific to the402.ai platform. It doesn't mention rate limits, error conditions, or response format, but covers the essential safety and authentication context well for a simple 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?

The description is perfectly concise and well-structured: two sentences that each earn their place. The first sentence states the core purpose, the second adds crucial context about usage and authentication requirements. There's zero wasted verbiage or 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?

For a zero-parameter tool with no annotations and no output schema, the description provides good contextual completeness. It explains what the tool does, what the balance represents, and authentication requirements. The main gap is the lack of information about return format or what the response contains, but given the tool's simplicity, this is a minor omission.

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 description coverage, so the baseline is 4. The description appropriately doesn't waste space discussing parameters that don't exist, which is efficient and correct. No additional parameter semantics are needed or provided.

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 purpose: checking a pre-funded USDC balance on the402.ai platform. It specifies the resource (balance) and context (used for purchases, service inquiries, and other paid operations via MCP server). However, it doesn't explicitly differentiate from sibling tools like 'balance_history' or 'provider_earnings', which prevents a perfect score.

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 some usage context by stating the balance is used for purchases and paid operations, and mentions it requires an API key. However, it doesn't explicitly guide when to use this tool versus alternatives like 'balance_history' (which might show transaction history) or 'provider_earnings' (which might show earnings rather than balance). The guidance is implied 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?

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it's a creation/mutation tool (implied by 'Create'), requires specific permissions ('Requires API key (provider account)'), and mentions billing periods. However, it lacks details on rate limits, error handling, or what happens on success/failure.

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 appropriately sized with three sentences that are front-loaded with the core purpose. Each sentence adds value: the first states the action, the second explains bundling and pricing, and the third covers prerequisites. There is no wasted text.

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 (a creation tool with 5 required parameters), no annotations, and no output schema, the description is moderately complete. It covers the purpose, context, and prerequisites but lacks details on return values, error cases, or operational constraints like rate limits, which would be helpful 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 all parameters thoroughly. The description adds minimal value beyond the schema by implying that 'service_ids' correspond to 'your services' and 'price' is 'recurring', but does not provide additional syntax or format details. Baseline 3 is appropriate when 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 specific action ('Create a subscription plan'), identifies the resource ('as a provider on the402.ai'), and distinguishes from siblings by mentioning bundling services at recurring prices, which differentiates it from tools like 'create_service' or 'manage_plan'.

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 context for when to use this tool ('as a provider' and 'Bundle one or more of your services at a recurring price'), and mentions that 'Agents can subscribe for monthly or annual access', which implies usage scenarios. However, it does not explicitly state when not to use it or name specific alternatives among siblings.

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 full burden. It discloses that this is a write operation ('List a new service'), requires authentication ('Requires API key'), and has a global effect ('discoverable by AI agents worldwide'). However, it doesn't mention potential side effects (e.g., if listing fails), rate limits, or error conditions, leaving behavioral gaps for a mutation 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?

The description is front-loaded with the core purpose in the first sentence, followed by supporting details. It's appropriately sized (three sentences) with minimal waste, though 'the the402.ai' has a typo ('the' duplicated). Each sentence adds value: action, parameters, and authentication requirement.

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 (11 parameters, mutation operation, no annotations, no output schema), the description is moderately complete. It covers purpose, key parameters, and authentication, but lacks details on return values, error handling, or operational constraints. For a creation tool with rich input schema, it's adequate but has clear gaps in behavioral context.

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 all 11 parameters thoroughly. The description lists some parameters (name, description, pricing, category, input requirements) but doesn't add meaning beyond what the schema provides—it merely echoes them without explaining interactions or constraints. 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 ('List a new service') and the resource ('on the the402.ai marketplace as a provider'), with specific details about what gets defined (name, description, pricing, etc.). It distinguishes from siblings like 'update_service' or 'delete_service' by focusing on creation, but doesn't explicitly contrast with other creation tools like 'create_plan'.

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 ('as a provider', 'discoverable by AI agents worldwide') and mentions a prerequisite ('Requires API key (provider account)'), but doesn't explicitly state when to use this versus alternatives like 'create_plan' or 'manage_product'. It provides some guidance but lacks clear when/when-not directives.

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 adds useful context about refund possibilities and API key requirements, which aren't in the schema. However, it lacks details on side effects (e.g., thread status changes), error conditions, or response format, leaving gaps for a mutation 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?

The description is appropriately sized with three sentences that each add value: action definition, user roles/refund context, and authentication requirement. It's front-loaded with the core purpose. Minor room for improvement in flow, but overall efficient.

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 mutation tool with no annotations and no output schema, the description provides basic operational context (refunds, API key) but lacks completeness. It doesn't cover success/error responses, idempotency, or system state changes, which are important for an agent to use this 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 the schema already documents both parameters thoroughly. The description doesn't add any meaningful semantic details about the parameters beyond what's in the schema (e.g., format of thread_id, examples of reasons). Baseline 3 is appropriate as 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 action ('Cancel or decline') and resource ('a thread on the402.ai'), making the purpose evident. However, it doesn't explicitly differentiate this tool from potential siblings like 'delete_service' or 'update_service' that might also modify thread states, missing full sibling distinction.

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 some implied context by stating 'Either the agent or provider can use this' and mentioning refund conditions, but it doesn't give explicit guidance on when to use this tool versus alternatives like 'accept_proposal' or 'send_message' for thread management. No clear when-not-to-use or alternative tool references are included.

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 full burden and excels by disclosing critical behavioral traits: permanence ('This is permanent'), consequences ('will no longer be discoverable or purchasable'), and authentication requirements ('Requires API key (service owner only)'), which are essential for safe tool invocation.

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 front-loaded with the core action, followed by critical behavioral details in two concise sentences. Every sentence adds value without redundancy, making it efficient 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?

For a destructive tool with no annotations or output schema, the description is highly complete—covering purpose, permanence, consequences, and auth needs. It could slightly improve by hinting at response format or error cases, but it's largely sufficient given 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?

The input schema has 100% description coverage, clearly documenting the 'service_id' parameter. The description does not add any additional meaning or context about the parameter beyond what the schema provides, meeting the baseline for 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 ('Remove') and target resource ('a service listing from the402.ai marketplace'), distinguishing it from sibling tools like 'update_service' or 'create_service'. It provides explicit scope and consequence.

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 stating it's for removing services from the marketplace and specifies prerequisites ('Requires API key (service owner only)'), but does not explicitly compare to alternatives like 'update_service' or indicate when not to use it.

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?

Since no annotations are provided, the description carries the full burden. It discloses key behavioral traits: it's a read-only operation ('View'), shows specific data fields (name, description, role, join date), and explicitly states 'No authentication required,' which is valuable context not covered elsewhere.

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 appropriately sized and front-loaded, consisting of a single, efficient sentence that conveys the purpose, data shown, and authentication requirement without any wasted words or 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 tool's low complexity (one parameter, no output schema, no annotations), the description is fairly complete. It covers what the tool does, what data it returns, and authentication needs. However, it lacks details on potential errors or the exact format of the return values, which could be helpful 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?

The input schema has 100% description coverage, with the parameter 'participant_id' fully documented. The description does not add any additional meaning or details about the parameter beyond what the schema provides, so it meets the baseline 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 clearly states the tool's purpose with a specific verb ('View') and resource ('participant's public profile on the402.ai'), and it distinguishes from siblings by specifying it shows profile information rather than performing actions like 'create_plan' or 'update_service'.

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 context for when to use this tool (to view a participant's public profile) and mentions 'No authentication required,' which helps in usage decisions. However, it does not explicitly state when not to use it or name alternatives among siblings, such as 'get_service' or 'get_thread'.

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 discloses key behavioral traits: 'No authentication required,' which is crucial for access. It also hints at the tool's scope (health, status, endpoints, referral details) but doesn't specify rate limits, response format, or potential side effects like caching 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 appropriately sized and front-loaded: the first sentence states the core purpose, the second adds usage context, and the third provides critical behavioral info. Every sentence earns its place with no wasted words, 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?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is fairly complete. It covers purpose, usage, and authentication needs. However, it lacks details on output format (e.g., what data is returned for 'health' or 'endpoints') and doesn't mention potential errors or limitations, which could be helpful 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?

The input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description adds value by confirming this implicitly through its focus on general platform info without mentioning any parameters. Baseline is 3 for high schema coverage, but the description compensates by aligning with the parameter-free nature.

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 purpose: 'Get the402.ai platform health, status, available endpoints, and referral program details.' It specifies the verb 'Get' and the resource 'platform info' with concrete details. However, it doesn't explicitly differentiate from sibling tools like 'check_balance' or 'provider_earnings', which might also provide platform-related information.

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 context for when to use it: 'Useful for understanding what the platform offers and how to get started.' It implies this is a general information tool for onboarding or status checks. However, it doesn't explicitly state when not to use it or name alternatives among siblings, such as 'check_balance' for financial status.

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 effectively describes key traits: it's a read operation ('Get'), specifies the return data structure (pricing, input schema, etc.), and explicitly states 'No authentication required'. However, it doesn't mention potential errors, rate limits, or response format details, leaving some behavioral aspects uncovered.

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 front-loaded with the core purpose in the first sentence, followed by specific return details and authentication note. Every sentence earns its place by adding critical information without redundancy, making it efficient 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 low complexity (1 parameter, no output schema, no annotations), the description is largely complete: it covers purpose, return data, and authentication. However, without an output schema, it could benefit from more detail on response structure or error handling, but it's sufficient for basic use.

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 the single parameter 'service_id'. The description adds no additional meaning beyond what's in the schema (e.g., format examples or ID sourcing). With high schema coverage, the baseline is 3, and the description doesn't compensate with extra parameter insights.

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 verb 'Get' and resource 'full details for a specific service on the402.ai by its ID', distinguishing it from siblings like browse_products or search_catalog. It specifies the exact scope of information returned (pricing, input schema, deliverable schema, etc.), making the purpose unambiguous.

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 by stating 'by its ID' and 'No authentication required', but does not explicitly say when to use this tool versus alternatives like inquire_service or get_platform_info. It provides basic context but lacks explicit guidance on when-not-to-use or direct comparisons with sibling tools.

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 of behavioral disclosure. It mentions 'Requires API key' for authentication, which is useful, but lacks details on rate limits, error handling, or what 'full details' entail (e.g., pagination, data format). For a read operation with no annotations, this is insufficient to fully inform an agent.

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 core purpose stated first. It uses two sentences efficiently: one for the tool's function and one for the authentication requirement. There is no unnecessary fluff, though it could be slightly more structured by explicitly separating usage notes.

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 (a read operation with one parameter) and lack of annotations or output schema, the description is moderately complete. It covers the purpose and authentication need but omits details on return values, error cases, and behavioral traits like rate limits. This leaves some gaps for an agent to operate effectively.

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 100% description coverage, with 'thread_id' documented as 'The thread ID'. The description does not add any parameter-specific semantics beyond this, such as format examples or validation rules. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.

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 purpose: 'Get full details and message history for a specific thread on the402.ai.' It specifies the verb ('Get') and resource ('thread'), and details the content ('conversation between agent and provider, including any price proposals, status updates, and delivery information'). However, it does not explicitly differentiate from sibling tools like 'list_threads' or 'get_participant', which prevents a score of 5.

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 minimal usage guidance: 'Requires API key' indicates a prerequisite, but it does not specify when to use this tool versus alternatives (e.g., 'list_threads' for summaries or 'get_participant' for user details). No explicit context or exclusions are mentioned, leaving gaps in when this tool is appropriate.

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 adds useful context: it mentions a cost ('Costs $0.001 from your pre-funded balance') and a prerequisite ('Requires API key'), which are not covered by annotations. However, it lacks details on response format, error handling, or other operational traits.

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 appropriately sized and front-loaded, with three concise sentences that each earn their place: stating the purpose, cost, usage context, and prerequisites without 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 complexity (a transactional tool with cost and prerequisites), no annotations, and no output schema, the description is fairly complete. It covers purpose, usage, cost, and prerequisites, but could benefit from mentioning response expectations or error cases to be fully comprehensive.

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 both parameters fully. The description does not add any meaning beyond what the schema provides for 'service_id' or 'brief', such as examples or constraints. Baseline 3 is appropriate when 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's purpose: 'Open a conversation thread about a service on the402.ai.' It specifies the action (open a conversation thread) and resource (service), but does not explicitly differentiate it from sibling tools like 'send_message' or 'get_thread' in terms of scope or intent.

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 context for when to use this tool: 'to ask questions, request custom quotes, or start a negotiation with a provider before purchasing.' It implies usage for pre-purchase inquiries, but does not explicitly state when not to use it or name alternatives among sibling tools.

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 that no authentication is required, which is useful behavioral context. However, it lacks details on rate limits, error handling, response format, or whether this is a read-only operation (implied by 'browse' but not explicit). The description adds some value but leaves gaps for a tool with no 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 efficiently structured in three sentences: purpose definition, plan details, and authentication note. Each sentence adds value without redundancy, making it easy to parse and front-loaded with key 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 no annotations and no output schema, the description provides basic context (purpose, authentication) but lacks details on behavioral traits like pagination behavior, return format, or error conditions. For a simple list tool with 2 parameters, it's minimally adequate but could be more complete to compensate for missing structured data.

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 fully documents the two parameters (limit and offset). The description doesn't add any parameter-specific information beyond what's in the schema, such as default values or usage tips. This meets the baseline of 3 when schema coverage is high.

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 purpose: 'Browse subscription plans on the402.ai' with specific details about what plans are (bundles of services at recurring prices) and what subscribing entails. It distinguishes from siblings like 'subscribe_to_plan' by focusing on browsing rather than subscribing, but doesn't explicitly differentiate from 'browse_products' or 'search_catalog' which might overlap.

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 stating 'No authentication required,' suggesting this is a public-facing tool. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'browse_products' or 'search_catalog,' nor does it mention prerequisites or exclusions beyond the authentication note.

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 discloses the requirement 'Requires API key' for authentication and hints at behavior by mentioning 'download status', which adds context beyond a basic list. However, it lacks details on rate limits, pagination, error handling, or whether this is a read-only operation (implied by 'List' but not explicit).

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 front-loaded with the core purpose in the first sentence, followed by additional context and a requirement. Every sentence earns its place: the first defines the action, the second adds scope, and the third specifies prerequisites. It's efficient with no wasted words, making it easy for an AI agent to parse quickly.

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 annotations, no output schema, and zero parameters, the description provides basic completeness by stating purpose, scope, and authentication needs. However, for a tool that likely returns a list of purchases, it doesn't explain return values (e.g., format, fields like product names or dates), which could be helpful since there's no output schema. It's adequate but has gaps in behavioral context.

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 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add parameter-specific information, which is appropriate here. Baseline is 4 for zero parameters, as there's nothing to compensate for and the description doesn't introduce confusion.

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 verb 'List' and resource 'purchased digital products on the402.ai', specifying scope with 'Shows products you've bought with download status'. It distinguishes from sibling tools like 'browse_products' and 'search_catalog' by focusing on user purchases rather than general catalog browsing. However, it doesn't explicitly contrast with 'purchase_product' or 'verify_delivery', which are related but distinct operations.

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 stating 'Requires API key' and focusing on user purchases, suggesting it's for viewing purchase history rather than browsing or buying. However, it doesn't explicitly state when to use this tool versus alternatives like 'balance_history' for financial tracking or 'verify_delivery' for delivery status, nor does it provide exclusions or prerequisites beyond the API key.

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 full burden. It discloses authentication requirement ('Requires API key') and scope (threads where user is agent or provider), but doesn't mention pagination behavior, rate limits, error conditions, or what the response format looks like. It adds some context but leaves significant behavioral aspects unspecified.

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?

Three sentences with zero waste: first states purpose, second adds filtering context, third specifies authentication requirement. Appropriately sized and front-loaded with the core functionality.

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 list tool with 3 parameters, 100% schema coverage, but no annotations and no output schema, the description provides basic purpose and authentication context but lacks information about response format, pagination details, or error handling. It's minimally adequate but has clear gaps in behavioral transparency.

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 all parameters thoroughly. The description mentions filtering by status but doesn't add meaning beyond what the schema provides about the enum values or other parameters. Baseline 3 is appropriate when 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 verb ('List') and resource ('conversation threads on the402.ai'), specifying it shows threads where the user is agent or provider. It doesn't explicitly distinguish from sibling tools like 'get_thread' or 'decline_thread', but the listing purpose is unambiguous.

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 by mentioning filtering by status to find active, completed, or disputed threads, but doesn't explicitly state when to use this tool versus alternatives like 'get_thread' (for single thread details) or 'list_purchases' (different resource). No explicit when-not or alternative guidance is provided.

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 discloses key behavioral traits: it's a mutation tool (implied by 'update or delete'), requires specific permissions ('Only the provider who created the plan can modify it'), and needs authentication ('Requires API key (plan owner)'). However, it lacks details on side effects, error handling, or response format, leaving gaps in transparency.

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 highly concise and front-loaded, consisting of two sentences that efficiently convey purpose and prerequisites. Every sentence adds value without redundancy, making it easy to parse and understand quickly.

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 (mutation with permissions), lack of annotations, and no output schema, the description is moderately complete. It covers purpose and prerequisites but omits details on behavior, return values, or error cases. For a mutation tool, this leaves room for improvement in guiding the agent fully.

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 detailed parameter documentation. The description adds no additional parameter semantics beyond what's in the schema. With high coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract from the schema's completeness.

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 purpose: 'Update or delete a subscription plan on the402.ai.' It specifies the verb ('update or delete') and resource ('subscription plan'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'create_plan' or 'list_plans', though the action distinction is implied.

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 context for when to use this tool: for modifying existing plans, with prerequisites ('Only the provider who created the plan can modify it. Requires API key (plan owner).'). It doesn't explicitly state when not to use it or name alternatives like 'create_plan' for new plans, but the context is sufficient for informed usage.

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 that it requires an API key for provider accounts, which is useful context. However, it doesn't mention other behavioral traits like rate limits, error handling, or what happens on deletion (e.g., if data is permanently removed). The description doesn't contradict annotations, but it lacks comprehensive behavioral details for a mutation 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?

The description is front-loaded with the core purpose in the first sentence, followed by clarifying details. Every sentence earns its place: the first defines actions and context, the second specifies product types, and the third states prerequisites. No wasted words, and it's 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 annotations and no output schema, the description provides basic context (purpose, provider requirement, product types) but lacks details on behavioral aspects like mutation effects, error cases, or response format. For a tool with 6 parameters and mutation actions, this is adequate but has clear gaps, especially around output and operational constraints.

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 all parameters thoroughly. The description adds minimal value beyond the schema—it mentions 'digital goods (files, datasets, templates)' which gives context for the 'product' resource but doesn't elaborate on parameter usage or constraints. Baseline 3 is appropriate as 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's purpose: 'Create, update, or delete a digital product on the402.ai as a provider.' It specifies the resource (digital product), the actions (create/update/delete), and distinguishes it from siblings like 'browse_products' or 'purchase_product' by focusing on provider-side management rather than browsing or purchasing.

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 context: 'as a provider' and 'Requires API key (provider account),' indicating when to use this tool (for provider operations). It doesn't explicitly state when not to use it or name alternatives, but the provider context implicitly distinguishes it from consumer tools like 'purchase_product' or 'browse_products.'

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 full burden and adds valuable behavioral context: it explains the effect of cancellation ('still gives access until the current period ends'), discloses an authentication requirement ('Requires API key'), and clarifies the meaning of different actions. However, it doesn't mention rate limits or error conditions.

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 efficiently structured in three sentences: the core purpose, important behavioral detail about cancellation, and authentication requirement. Every sentence adds essential information with zero 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 mutation tool with no annotations and no output schema, the description provides good coverage of the tool's behavior and authentication needs. However, it doesn't describe the return format or error responses, leaving some gaps in completeness.

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 both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score for 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 ('cancel, pause auto-renewal, or resume a paused subscription') on a specific resource ('your subscription on the402.ai'), distinguishing it from sibling tools like 'subscribe_to_plan' or 'manage_plan' which handle different subscription-related operations.

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 context for when to use this tool ('Manage your subscription'), but doesn't explicitly state when not to use it or name specific alternatives among the sibling tools, though the distinction from 'subscribe_to_plan' is implied.

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 key behavioral traits: it's a provider action only, free, and requires an API key. However, it lacks details on rate limits, error handling, or what happens if the price is invalid, leaving some gaps in transparency for a mutation 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?

The description is front-loaded with the core purpose, followed by usage context and key constraints, all in three efficient sentences with zero wasted words. It's appropriately sized and well-structured for quick comprehension.

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 (a mutation with 3 parameters, no annotations, and no output schema), the description is adequate but incomplete. It covers the action and basic constraints but lacks details on return values, error cases, or deeper behavioral aspects, making it minimally viable but with clear gaps.

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 all parameters thoroughly. The description doesn't add any additional meaning or context beyond what the schema provides, such as explaining the relationship between parameters or usage tips, resulting in a 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 clearly states the action ('proposes a price') and resource ('for a thread on the402.ai'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'accept_proposal' or 'send_message' in terms of negotiation flow, which prevents a perfect score.

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 context on when to use this tool ('After discussing requirements with the agent') and mentions the subsequent actions ('agent can then accept and pay, or continue negotiating'), giving good guidance. It doesn't explicitly state when not to use it or name alternatives among siblings, so it falls short of a 5.

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 clearly indicates this is a read-only operation ('View'), specifies authentication requirements ('Requires API key (provider account)'), and describes the data structure (shows settled, held, and pending amounts). However, it doesn't mention potential rate limits, error conditions, or whether the data is real-time vs cached. For a tool with zero annotation coverage, this provides basic but incomplete behavioral 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 extremely concise and front-loaded with the core purpose in the first clause. Every sentence earns its place: the first states what the tool does, the second specifies the data breakdown, and the third provides critical authentication context. There is zero waste or 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 tool has no parameters, no output schema, and no annotations, the description provides adequate basic information about what the tool does and authentication requirements. However, for a financial data tool, it could benefit from mentioning data freshness, whether amounts are in a specific currency, or what format the breakdown is presented in. The description is complete enough to understand the tool's purpose but leaves some contextual questions unanswered.

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 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, which is correct. No additional parameter semantics are needed or provided.

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 purpose: 'View your provider earnings breakdown on the402.ai' with specific resource (provider earnings) and scope (breakdown of settled, held, pending amounts). It distinguishes from siblings like 'check_balance' or 'balance_history' by focusing specifically on provider earnings rather than general balance or transaction history. However, it doesn't explicitly contrast with these specific siblings.

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 context for when to use this tool: when needing to view provider earnings breakdown. It specifies the requirement of 'API key (provider account)' which indicates prerequisites. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools, though the context implies this is for provider earnings specifically.

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 and does well by disclosing key behavioral traits: payment method (deducted from pre-funded balance), post-purchase workflow (use list_purchases to find/download), and authentication requirement (requires API key). It doesn't mention rate limits or error conditions, but covers essential operational 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?

Three tightly focused sentences with zero waste: first states the core action, second explains payment mechanics, third provides post-purchase guidance and authentication requirement. Every sentence earns its place by adding distinct value.

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 single-parameter mutation tool with no annotations and no output schema, the description provides good coverage of the operation's purpose, payment mechanism, and workflow. It could be more complete by mentioning potential error cases or return values, but covers the essential context well given 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?

With 100% schema description coverage, the schema already fully documents the single 'product_id' parameter. The description doesn't add any additional parameter semantics beyond what's in the schema, so it meets the baseline expectation for 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 ('Purchase a digital product') and resource ('on the402.ai'), distinguishing it from siblings like 'purchase_service' or 'browse_products'. It specifies the exact nature of the transaction (digital product purchase with pre-funded balance).

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 context about when to use this tool (for purchasing digital products) and mentions a related tool ('list_purchases') for post-purchase actions. However, it doesn't explicitly contrast when to use this versus alternatives like 'purchase_service' or 'subscribe_to_plan'.

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 and does this well. It explains the async job creation, conversation thread creation, payment deduction from pre-funded balance, immediate vs asynchronous result delivery based on service type, and authentication requirement ('Requires API key'). It doesn't mention rate limits or error conditions, but covers most key behavioral aspects.

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 efficiently structured with four sentences that each earn their place: states the core action, explains the process flow, describes different service type behaviors, and notes authentication requirement. It's front-loaded with the main purpose and contains zero 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 complexity of a purchase tool with no annotations and no output schema, the description does a good job covering key aspects: purpose, process flow, payment mechanism, service type variations, and authentication. It could benefit from mentioning what the tool returns (e.g., job ID, thread ID) or error conditions, but it's reasonably complete for the context.

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 baseline is 3. The description doesn't add significant meaning beyond what the schema already provides for the two parameters. It mentions that the brief 'must include all required fields defined in the service's input_schema' which slightly elaborates on the schema's description, but this is minimal additional 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 ('Purchase a fixed-price service') and resource ('on the402.ai'), distinguishing it from sibling tools like purchase_product (which likely purchases products rather than services) or create_service (which creates rather than purchases services). The description provides concrete details about what the tool does beyond just the name.

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 context about when to use this tool ('Purchase a fixed-price service') and mentions different service types (data_api vs automated/human services) with their respective behaviors. However, it doesn't explicitly state when NOT to use this tool or name specific alternatives among the many sibling tools, though the distinction from purchase_product is implied.

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 discloses that it 'Requires API key' (auth needs) and mentions earnings percentages, but lacks details on rate limits, error handling, or what 'withdraw' entails (e.g., fees, timing). For a tool with mutation actions like 'withdraw,' this is insufficient behavioral 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 appropriately sized and front-loaded, starting with the core purpose. It uses bullet-like formatting for actions, which is efficient. However, the earnings percentages could be integrated more smoothly, and the sentence structure is slightly cluttered.

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 annotations and no output schema, the description partially compensates by explaining actions and auth needs. However, for a tool with mutation capabilities (e.g., 'withdraw'), it lacks details on return values, error cases, or side effects, leaving gaps in completeness.

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 'action' parameter fully documented in the schema. The description adds minimal value by listing the actions in a slightly different format, but doesn't provide additional semantics beyond what the schema already covers. 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 tool's purpose: 'Manage your referral program on the402.ai' with specific actions listed. It distinguishes itself from siblings by focusing on referral management, which is unique among the listed tools. However, it doesn't explicitly contrast with similar tools (none exist in siblings), so it's not a perfect 5.

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 through 'Manage your referral program' and 'Requires API key,' suggesting when to use it. However, it lacks explicit guidance on when to choose this tool over alternatives (though no direct alternatives exist in siblings) or any exclusions. The guidelines are present but not comprehensive.

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 full burden and does well by disclosing key behavioral traits: it describes the return format ('service listings with pricing, descriptions, and provider reputation scores') and explicitly states 'No authentication required.' However, it doesn't mention rate limits, pagination behavior beyond parameters, or error conditions.

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?

Three efficient sentences with zero waste: first states purpose, second details search dimensions, third covers returns and authentication. Every sentence earns its place and information is front-loaded appropriately.

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 search tool with no annotations and no output schema, the description provides good coverage: purpose, usage context, return format, and authentication requirements. It could be more complete by mentioning pagination behavior or result format details, but covers the essentials well given 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 description coverage is 100%, so the schema already fully documents all 7 parameters. The description adds marginal value by mentioning the searchable dimensions (keyword, category, service type, price range) but doesn't provide additional semantic context beyond what's in the parameter descriptions.

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'), target resource ('the402.ai service marketplace'), and what it finds ('AI agent services'). It distinguishes this search tool from browsing or listing tools among siblings by focusing on keyword/category/price filtering.

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 context for when to use this tool ('Find AI agent services by keyword, category, service type, or price range'), but doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools like 'browse_products' or 'list_services' (if such existed).

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 adds useful context about being free with no balance deduction and requiring an API key, which are not in the schema. However, it doesn't cover other behavioral aspects like response format, error handling, or rate limits, leaving gaps for a mutation 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?

The description is appropriately sized and front-loaded, starting with the core purpose. Each sentence adds value: the first defines the tool, the second gives usage examples, and the third covers cost and authentication. There's minimal waste, though it could be slightly more structured for clarity.

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 2 parameters with full schema coverage, no output schema, and no annotations, the description is moderately complete. It covers purpose, usage examples, cost, and authentication, but as a mutation tool, it should ideally include more behavioral details like response expectations or error cases to be fully adequate.

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 description coverage is 100%, so the schema already documents both parameters ('thread_id' and 'message') adequately. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or constraints, resulting in a 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 clearly states the action ('Send a message') and resource ('in a thread on the402.ai'), specifying it works for both agents and providers. However, it doesn't explicitly differentiate from sibling tools like 'decline_thread' or 'get_thread', which also involve thread interactions but for different purposes.

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 implied usage context by listing examples ('communicate about requirements, provide updates, ask questions, or share information') and notes it's free with no balance deduction. However, it lacks explicit guidance on when to use this tool versus alternatives like 'decline_thread' or 'inquire_service', and doesn't mention prerequisites beyond the API key requirement.

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 effectively describes key traits: it's a transactional tool ('Pays... from your pre-funded balance'), has temporal effects ('until the period ends'), includes auto-renewal, and requires authentication ('Requires API key'). It lacks details on error handling or rate limits, but covers essential behavior for a subscription 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?

The description is front-loaded with the core action and resource, followed by key details in a logical flow: payment method, access duration, renewal policy, and authentication requirement. Every sentence adds value without redundancy, making it efficient 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 complexity (a financial transaction with auto-renewal), no annotations, and no output schema, the description provides a solid foundation by covering purpose, payment, access, renewal, and authentication. It could be more complete by mentioning response format or error cases, but it adequately addresses the core context for agent use.

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 'plan_id' fully documented in the schema. The description does not add any additional meaning or context about the parameter beyond what the schema provides, such as example values or constraints. This meets the baseline score when schema coverage is high.

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 ('Subscribe to a plan') and resource ('on the402.ai'), distinguishing it from siblings like 'list_plans' or 'manage_subscription'. It specifies the outcome ('Gives access to all services bundled in the plan until the period ends') and mechanism ('Pays the first billing period from your pre-funded balance'), making the purpose unambiguous.

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 stating 'Requires API key', which suggests authentication prerequisites. However, it does not explicitly guide when to use this tool versus alternatives like 'purchase_product' or 'manage_subscription', nor does it specify exclusions or direct comparisons to sibling tools.

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 full burden for behavioral disclosure. It mentions 'Requires API key' for authentication, which adds value, but lacks details on rate limits, whether updates are reversible, what happens to unspecified fields, or error handling. For a mutation tool with zero annotation coverage, this is insufficient.

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 front-loaded with the main purpose and efficiently lists updatable fields in a single sentence, followed by a prerequisite note. It avoids unnecessary words, though it could be slightly more structured by separating the authentication requirement.

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 annotations and no output schema, the description is moderately complete for a simple update tool but lacks details on behavioral traits like side effects or response format. It covers the basic purpose and authentication need, but gaps remain for an agent to use it confidently without trial and error.

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 all three parameters. The description adds no additional meaning beyond implying that 'other profile fields' might exist, but doesn't specify them or provide syntax details. Baseline 3 is appropriate when 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 action ('Update your participant profile') and resource ('on the402.ai'), specifying what fields can be changed ('display name, description, or other profile fields'). It distinguishes from siblings like 'get_participant' (read vs. write) but doesn't explicitly differentiate from other update tools like 'update_service'.

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 profile changes are needed and mentions a prerequisite ('Requires API key'), but doesn't specify when to use this versus alternatives like 'manage_plan' or 'update_service', nor does it provide exclusions or context about when not to use it.

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 discloses that the tool requires an API key and is restricted to service owners, which is crucial for permissions. However, it lacks details on mutation behavior (e.g., partial updates, validation, error handling, or response format), leaving gaps for an agent to infer.

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 with zero waste: the first states the purpose and scope, and the second specifies prerequisites. It is front-loaded with the core functionality, making it 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?

For a mutation tool with 9 parameters, no annotations, and no output schema, the description is incomplete. It covers authentication needs but lacks details on behavioral traits (e.g., idempotency, side effects) and output expectations. Given the complexity, it should provide more guidance on usage and results.

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 fully documents all 9 parameters. The description adds minimal value beyond the schema by listing examples of fields that can be changed ('price, description, status, or any other field'), but does not provide additional syntax, constraints, or usage context for parameters.

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 verb ('Update') and resource ('an existing service listing on the402.ai'), with specific examples of what can be changed ('price, description, status, or any other field'). It distinguishes from sibling tools like 'create_service' (for new listings) and 'delete_service' (for removal).

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 context for when to use this tool: to modify an existing service listing. It implicitly contrasts with 'create_service' for new listings, but does not explicitly mention when not to use it or name specific alternatives among siblings like 'manage_service' or 'update_profile'.

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 and does well by disclosing key behavioral traits: it's a financial transaction ('releases the escrow payment'), has a cost ('Costs $0.001 from balance'), and requires authentication ('Requires API key'). It doesn't mention rate limits or error handling, but covers the essential mutation and security aspects.

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 efficiently structured in three sentences that each add value: states the action, specifies cost, and provides usage prerequisites. It is front-loaded with the core purpose and has 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 mutation tool with no annotations and no output schema, the description is reasonably complete: it explains the action, cost, and prerequisites. However, it lacks details on response format or error conditions, which would be helpful given the financial nature of the 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?

Schema description coverage is 100% for the single parameter 'thread_id', so the schema already documents it fully. The description adds no additional parameter semantics beyond what the schema provides, meeting the baseline for high 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 ('confirms that delivery is satisfactory and releases the escrow payment to the provider') and resource (delivery/escrow payment). It distinguishes from siblings like 'decline_thread' or 'send_message' by focusing on payment release after delivery verification.

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 context for when to use this tool ('Only use after reviewing the delivered work'), which implicitly distinguishes it from tools like 'decline_thread' or 'propose_price'. However, it does not explicitly name alternatives or specify when NOT to use it.

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