InsureLink

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 describes the output content (capability manifest with specific details) but lacks behavioral traits such as performance characteristics, error handling, or data freshness. The description does not contradict any annotations, but it misses opportunities to disclose operational aspects beyond the return data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that efficiently lists all key components of the returned manifest. It is front-loaded with the main action and resource, with no redundant or verbose language, making it highly concise 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 complexity (metadata retrieval with no inputs) and lack of annotations and output schema, the description is moderately complete. It specifies what information is included in the manifest but does not detail the format, structure, or potential limitations of the returned data, leaving gaps for an agent to infer usage.

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 schema fully documents the absence of inputs. The description adds no parameter-specific information, which is appropriate here. A baseline of 4 is applied as it compensates adequately for the lack of parameters by focusing on output semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Returns') and the specific resource ('full InsureLink capability manifest'), listing concrete components like actions, tokens, pricing, protection schedule, and framework compatibility. It distinguishes itself from siblings by focusing on system metadata rather than operational functions like 'mint_sla' or 'get_activity'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying what information is returned (e.g., supported actions, pricing), suggesting it should be used to understand system capabilities before invoking other tools. However, it does not explicitly state when to use it versus alternatives or provide exclusion criteria, leaving some ambiguity about its priority in workflows.

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 discloses key behavioral traits: it's a mutation (exiting), requires payment, and returns payment instructions. It adds value beyond the schema by explaining costs and output behavior, though it could detail more about the protection adjustment 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 appropriately sized with three concise sentences that are front-loaded: it states the action, cost, and return value efficiently, with no 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 complexity (mutation with payment), no annotations, and no output schema, the description is fairly complete by covering purpose, cost, and output. However, it lacks details on the protection adjustment mechanism or potential side effects, leaving some gaps for a mutation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the schema already documents the tokenId parameter. The description does not add meaning beyond the schema, such as explaining what tokenId represents or its format, 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 ('Exits an SLA early') and specifies the mechanism ('with protection adjustment'), distinguishing it from siblings like renew_sla or mint_sla. It uses precise verbs and identifies the resource (SLA) effectively.

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 ('Exits an SLA early') and implies a financial prerequisite ('Requires x402 payment'), but does not explicitly state when not to use it or name alternatives among siblings like renew_sla or micro_reset.

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 returns data but doesn't specify what 'recent' means (e.g., time range), whether the data is paginated, if authentication is required, or any rate limits. This leaves significant behavioral gaps for a tool that likely accesses transactional data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's appropriately sized for a simple tool and front-loads the core purpose immediately, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'platform transactions' entail, the format of the returned data, or any behavioral constraints. For a tool that returns data without structured output documentation, this leaves too many contextual 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?

The schema description coverage is 100%, with the 'limit' parameter fully documented in the schema. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score of 3 for adequate but not additive parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Returns recent platform transactions' clearly states the verb ('returns') and resource ('recent platform transactions'), making the tool's purpose understandable. However, it doesn't differentiate this tool from potential sibling tools that might also return transaction data, so it doesn't reach the highest 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 no guidance on when to use this tool versus alternatives. It doesn't mention any context, prerequisites, or exclusions, nor does it reference any sibling tools for comparison. This leaves the agent with minimal usage direction.

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 states the tool returns a ranked list but lacks details on format (e.g., structured data, pagination), freshness of data, rate limits, or authentication needs. For a read operation with zero annotation coverage, this leaves significant behavioral 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 a single, efficient sentence that front-loads the core functionality ('Returns the top 25 most reliable agents') with essential qualifiers ('ranked by reputation score'). Zero wasted words, perfectly sized for a no-parameter tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 0 parameters, the description adequately covers the basic purpose but lacks details on return format, data freshness, or error handling. For a simple read tool, it's minimally viable but incomplete for robust agent use without additional 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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description appropriately adds no parameter information, maintaining focus on the tool's purpose without redundancy. Baseline for 0 parameters is 4.

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 ('Returns') and resource ('top 25 most reliable agents ranked by reputation score'), distinguishing it from siblings like get_reputation (likely individual scores) or get_activity (different metric). It precisely defines scope and ranking criteria.

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 for retrieving top-ranked agents by reputation, but provides no explicit guidance on when to use this versus alternatives like get_reputation (for individual scores) or get_activity (for activity metrics). Usage context is inferred rather than stated.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns data, implying it is a read-only operation, but does not specify any behavioral traits such as rate limits, authentication needs, error handling, or what 'flags' might entail. For a tool with no annotation coverage, this is a significant gap 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 a single, efficient sentence that directly states the tool's function without any unnecessary words. It is front-loaded with the core purpose and avoids redundancy, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a single-parameter read operation) and the lack of annotations and output schema, the description is minimally complete. It covers what the tool returns but does not address behavioral aspects or usage context. For a simple tool, this is adequate but leaves gaps, warranting a middle score.

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 'wallet' parameter clearly documented as 'Wallet address (0x...)'. The description adds minimal value beyond this by implying the parameter is used to fetch reputation data, but it does not provide additional semantics like format constraints or examples. Given the high schema coverage, a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Returns reputation score, tier, stats, and flags for a wallet address.' It specifies the verb ('Returns') and the resource/scope ('reputation score, tier, stats, and flags'), making it easy to understand what the tool does. However, it does not explicitly differentiate from sibling tools like 'get_activity' or 'get_leaderboard', which might also retrieve wallet-related data, so it falls short of 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 no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, such as when to choose 'get_reputation' over 'get_activity' or other sibling tools. This lack of usage instructions leaves the agent without clear direction, making it a minimal score.

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 returns history but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, error conditions, or the format of the returned history (e.g., list of events, timestamps). This leaves significant gaps for a tool that retrieves historical data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy 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 the complexity of retrieving historical data, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'SLA history' entails (e.g., time range, event types), the return format, or behavioral constraints, leaving the agent with insufficient context for reliable 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?

The input schema has 100% description coverage, with the 'wallet' parameter clearly documented as 'Wallet address (0x...)'. The description adds no additional parameter semantics beyond this, so it meets the baseline score of 3 where 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 verb 'Returns' and the resource 'full SLA history for a wallet address', making the purpose specific and understandable. However, it doesn't differentiate this tool from potential sibling tools like 'get_activity' or 'get_reputation' that might also retrieve wallet-related data, preventing 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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the wallet must have an SLA), exclusions, or comparisons to siblings like 'get_activity' or 'get_reputation', leaving usage context unclear.

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 beyond the schema by specifying a payment requirement ($0.001) and that it returns payment instructions, which are behavioral traits. However, it doesn't cover other aspects like potential side effects, error conditions, or authentication needs, 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 appropriately sized with two sentences that are front-loaded with the main action and include essential details like payment and return values. There's minimal waste, though it could be slightly more structured for clarity, but overall it's 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?

Given the tool has no annotations, no output schema, and a simple input schema, the description is moderately complete. It covers the action, payment requirement, and return type, but lacks details on output format, error handling, or deeper behavioral context, which would be beneficial for full understanding.

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 the 'tokenId' parameter as 'SLA token ID'. The description doesn't add any further meaning or details about this parameter beyond what the schema provides, meeting the baseline for high schema coverage without extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Resets the insurance window') and resource ('for an SLA'), making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'renew_sla' or 'wrap_usdc', which might have overlapping domains, so it doesn't achieve full differentiation.

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 resetting an SLA's insurance window is needed, and mentions a payment requirement that could serve as a prerequisite. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'renew_sla' or other siblings, leaving the context somewhat implied rather than clearly defined.

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 key behavioral traits: creation action (implies mutation), payment requirement, and return type (payment instructions). However, it lacks details about permissions, rate limits, error conditions, or what happens after payment. The description adds value but doesn't fully compensate for the absence of 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 extremely concise with just two sentences that each serve distinct purposes: first states the core action, second adds crucial behavioral context (payment and return). No wasted words, front-loaded with the main purpose. Perfectly sized for this 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?

For a mutation tool with no annotations and no output schema, the description provides basic completeness: purpose, payment requirement, and return type. However, it lacks details about the SLA creation process, what the NFT represents, how payment instructions are used, or error handling. Given the complexity of blockchain/SLA operations, more context would be helpful.

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 parameter-specific information beyond what's in the schema. It mentions payment requirement which relates to the tool's behavior but doesn't explain parameter meanings, interactions, or constraints. 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 ('Creates a new ERC-721 SLA agreement NFT'), identifies the resource (SLA agreement NFT), and distinguishes it from sibling tools like 'renew_sla' or 'get_sla_history' by specifying it's a creation operation rather than renewal or querying. The mention of ERC-721 standard and payment requirement adds technical specificity.

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 x402 payment ($0.01)', which suggests this tool should be used when ready to pay for creating an SLA. However, it doesn't explicitly state when to use this versus alternatives like 'renew_sla' or provide clear exclusions. The guidance is 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's a mutation operation (implied by 'Renews'), requires payment ($0.005), and returns payment instructions. It doesn't cover rate limits, error conditions, or authentication needs, but provides essential context beyond basic purpose.

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 front-loaded: two sentences that each earn their place by stating the action, cost, and return value. There's zero wasted text, and information is presented in logical order (purpose → requirement → outcome).

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 completeness for a mutation tool with payment: it covers purpose, cost, and return type. However, it lacks details on error handling, what 'renew' actually does to the SLA, or format of payment instructions, leaving gaps for an agent to operate safely.

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 adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain 'tokenId' or 'duration' further). This meets the baseline of 3 for high schema coverage without extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Renews') and resource ('an existing SLA agreement'), making the purpose immediately understandable. It distinguishes from siblings like 'mint_sla' (creation) and 'get_sla_history' (read-only). However, it doesn't specify what 'renew' entails operationally beyond payment, leaving some ambiguity about the outcome.

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 an SLA needs renewal and payment is available, but provides no explicit guidance on when to use this vs. alternatives like 'mint_sla' for new agreements. It mentions a prerequisite ('Requires x402 payment') which gives some context, but lacks clear when/when-not scenarios or comparison 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 the full burden of behavioral disclosure. It adds useful context about the payment requirement and return of instructions, but it lacks details on permissions, rate limits, or potential side effects like transaction confirmation times. This is adequate but has clear 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 action, followed by key constraints and outcomes in just two sentences. Every sentence earns its place by providing essential information without any waste, making it highly 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 as a mutation with no annotations and no output schema, the description is minimally complete. It covers the action, cost, and return type, but lacks details on error handling, response format, or integration with sibling tools. This meets basic needs but leaves room for improvement.

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 the 'amount' parameter fully. The description doesn't add any additional meaning or examples beyond what the schema provides, such as clarifying the 'base units' format. 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 verb ('Wraps') and resource ('USDC into iUSDC'), making the purpose specific and understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'mint_sla' or 'renew_sla', which might involve similar financial operations, so it doesn't reach the highest 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 implies usage by mentioning 'Requires x402 payment ($0.001)', which suggests a context of cost, but it doesn't provide explicit guidance on when to use this tool versus alternatives or any exclusions. This leaves the agent with only implied context for decision-making.

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