Cybercentry Verification

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

With no annotations, the description carries the burden of behavioral disclosure and does so well. It explicitly lists what the tool detects, separately discloses issuer controls, and transparently states the cost and payment method ($1.00, USDC over x402). It does not contradict any annotations because none are provided.

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

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

The description is two sentences, front-loaded with the core purpose, and every sentence provides valuable information. There is no redundancy or fluff; the cost and payment details are included efficiently.

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?

The description explains what the tool does, when to use it, what it detects, and the cost. While there is no output schema, the description implies the output through phrases like 'detects' and 'discloses issuer controls.' It could be improved by explicitly mentioning the return format, but overall it is sufficiently complete for a verification 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 already provides 100% coverage with descriptions for all three parameters, so the baseline is 3. The tool description adds context about Base and B20 tokens, which indirectly clarifies the 'chain' parameter, but it does not add specific parameter-level semantics beyond the schema.

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 ('Check'), the resource ('Base token contract'), and the context ('before buying'). It details specific detection categories (honeypots, freeze-and-seize, pause, fake B20s, impersonation) and distinguishes itself from the sibling ethereum_token_verification by targeting the Base chain and B20 tokens.

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 gives a clear usage context ('before buying') and specifies the target chain (Base), implying when to use it. It also mentions the $1.00 cost, aiding decision-making. However, it does not explicitly state when not to use it or name alternative tools, leaving some ambiguity versus the similar Ethereum verification sibling.

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 explicitly states the cost ('$1.00 per call') and payment method ('USDC over x402'), which is critical for an agent deciding whether to invoke. It also mentions 'real-time threat intelligence,' implying live data access. This goes beyond what the schema provides.

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

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

The description is two sentences, front-loaded with the purpose in the first sentence and the cost in the second. Every word earns its place, with no 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?

For a simple Q&A tool with two parameters and no output schema, the description provides sufficient context: what the tool does, the topic scope, cost, and payment method. The optional subscription_token is documented clearly in the schema, so the description need not elaborate further. The agent has all necessary information to decide whether to use the tool.

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

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

The input schema covers 100% of the parameters (query and subscription_token) with descriptions. The description adds no parameter-specific information beyond what the schema already provides, so the baseline of 3 is appropriate. The schema is sufficient.

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 function: 'Ask a cyber security question and get an expert answer backed by real-time threat intelligence.' It uses a specific verb ('ask') and resource ('cyber security question'), and the scope ('current threats, best practice and compliance') distinguishes it from sibling verification tools, which are more narrowly focused.

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 the tool: whenever a cyber security question needs an expert answer. It does not explicitly mention alternatives or when not to use it, but the purpose is evident given the sibling list of specialized verification tools, making the usage context clear.

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 explicitly states the cost ($1.00 per call) and payment method (USDC over x402), which is critical for an agent to know. It also mentions the output as a scan report. It doesn't detail rate limits or failure modes, but the disclosed cost and payment are significant and responsibly disclosed.

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: two sentences that first state the primary purpose and specific checks, then the output and cost. Every word earns its place; there is no fluff or redundancy. It is highly efficient for an 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 the schema coverage and the absence of an output schema, the description provides sufficient context for an agent to know what the tool does and what it returns (a scan report). It mentions the checks performed and the cost. It doesn't describe the report structure in detail, but that may be acceptable for a verification tool. The lack of an output schema is slightly compensated by the explicit checks listed.

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 provides 100% description coverage for all parameters, so the baseline is 3. The description does not add any parameter-specific meaning beyond what the schema already states, such as the chain default or legacy parameters. No extra clarification or examples are provided, so it stays at baseline.

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

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

The description clearly states the tool's purpose: checking Ethereum or EVM token contracts for rug pull, hidden tax, liquidity legitimacy, and holder concentration risk before buying. It distinguishes itself from sibling tools like base_token_verification by specifying Ethereum/EVM chains, making its scope 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 gives clear context: use before buying a token to perform due diligence. It doesn't explicitly mention when not to use it or point to alternatives, but the purpose is well-defined and implies the appropriate scenario. The existence of sibling tools like base_token_verification suggests potential alternative routing, but this is not stated.

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

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

No annotations exist, so the description carries the burden. It adds 'Free' and 'every', providing some context, but does not disclose output format, pagination, or any other behavioral traits. For a simple list tool, this is adequate but not comprehensive.

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, front-loaded sentence that conveys purpose, content, and cost without any filler. Every word earns its place.

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

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

Given the tool's simplicity (no params, no output schema), the description covers the essential information: what it lists and that it is free. It could mention the return format, but for a zero-parameter list tool, this is nearly complete.

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, so there is nothing to explain beyond the schema. Baseline for 0 params is 4, and the description correctly focuses on what the tool returns.

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

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

Description states a specific verb ('List') and resource ('every Cybercentry verification service') with detailed content (price, inputs, SLA). This clearly distinguishes it from the sibling tools, which are individual verification services.

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?

Usage is implied: use this tool to list all services. However, it does not explicitly state when to use it versus alternatives (e.g., specific verification tools), nor does it provide exclusions.

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 must carry the burden. It discloses the $1.00 per-call cost and payment method (USDC over x402), which is important behavioral context, but it does not detail authentication requirements, failure modes, or whether any state is mutated. Verification is implied read-only.

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: features, application, cost. Every sentence adds distinct information, and the core purpose is in the first line.

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

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

With no output schema, the description doesn't clarify what the returned result looks like (e.g., a confidence score, a report, or a boolean). It also omits details on edge cases like unsupported formats. Still, it covers the core capabilities and pricing sufficiently for many use cases.

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 covers 100% of parameters with descriptions. The tool description adds context around C2PA and impersonation check, but does not explain each parameter beyond the schema. Defaults for booleans are in schema.

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

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

Description opens with an action verb 'Check' and specifies the resource 'image or video', then enumerates distinct capabilities (C2PA credentials, provenance/metadata, avatar/logo impersonation). This clearly differentiates it from sibling token/wallet verification tools.

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

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

The phrase 'before trusting it' gives clear context for when to apply the tool. However, it does not explicitly state when not to use it or point to alternative sibling tools for other verification needs.

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 must carry the full burden of behavioral disclosure. It reveals the pricing ($1.00 per call) but does not explain what the tool returns (e.g., a report, a pass/fail status, or a list of vulnerabilities), nor does it mention side effects, permission requirements, or whether it modifies the input. This lack of transparency is critical for an audit 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 consists of three concise sentences. The first sentence states the core purpose, the second provides the usage context, and the third gives pricing. Every sentence adds valuable information without redundancy or fluff, making it efficient and front-loaded.

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?

Despite having 6 parameters and no output schema, the description omits many details needed for an AI agent to use the tool effectively. It does not explain how to interpret the results, what each parameter does beyond the schema, or any dependencies (e.g., subscription token usage). The tool's complexity demands more context, especially regarding the output format and behavioral expectations.

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 6 parameters with 100% description coverage, so the schema already documents each parameter. The description adds no extra meaning beyond mentioning 'agent configuration' (the config parameter). Since the baseline is 3 when schema coverage is high, and the description does not degrade or improve understanding, a 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: 'Audit an AI agent configuration for security holes: prompt injection exposure, missing authentication, over-broad tool permissions and unsafe gateway settings.' It specifies the verb (audit/check) and the resource (AI agent configuration), and the specific security aspects differentiate it from the sibling tools (e.g., base_token_verification, web_application_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 a clear usage scenario: 'Check an agent before you trust it or connect to it.' This tells the agent when to invoke the tool. It also mentions the cost ($1.00 per call), which is relevant for decision-making. However, it does not explicitly state when not to use it or compare it to sibling tools, missing the opportunity to provide exclusions or alternatives.

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

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

No annotations exist, and the description carries the full burden well: it discloses the $1.00 per-call cost paid in USDC over x402, the per-call vs subscription quota tradeoff, the deliberate exclusion of price decline, and that uncomputable signals are named rather than silently scored clean. The confidence-separation note also warns against reading a high score on thin evidence as certainty.

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?

Front-loaded with what the tool does, then progressively adds constraints, cost, and caveats; nearly every sentence carries unique information. It runs slightly long and includes some rhetorical framing ('falling is not fraud', 'cannot read as a certainty') that could be tightened, but nothing is filler.

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

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

With no output schema and no annotations, the description supplies what an agent needs: the scoring range, the confidence companion value, the chain restriction, the attribution requirement, the explicit exclusion rule, and the billing model. Few gaps remain for a 4-parameter screening call.

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

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

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning beyond the schema: it explains why 'creator' matters (at most venues the token was deployed by the venue's own factory, so the creating address is the launchpad, not the applicant) and that omitting it leaves deployer signals unavailable. That is real guidance for a parameter the schema only labels.

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?

States a specific verb and resource ('Score a live token launch'), names the standard applied (ERC-8376), and specifies the output shape: a twelve-signal vector collapsed into a 0-100 abuse score with separately reported confidence. The word 'live' plus 'A screening, not a bonded on-chain report' implicitly separates it from pre_launch_screening without ambiguity.

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?

Clear about when the tool applies (a live/launched token), what it explicitly does not treat as abuse (price decline), and how to supply attribution via the creator argument. It stops short of naming pre_launch_screening as the alternative for tokens that have not launched yet, leaving that routing to inference from the tool name.

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, the description carries the full burden and delivers: cost ($1.00/call in USDC over x402), the optional subscription-token alternative, the depth limit (33 chains), and notably an honesty behavior ('says what it could not establish rather than reporting it clean'). It also discloses the ERC-8376 limitation that 8 of 12 signals cannot exist pre-sale, which is exactly the kind of caveat an agent needs.

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?

Front-loaded with the core purpose and organized into wallet-verification then launch-specific halves. It is dense and sentence-heavy in the middle, but nearly every clause carries substantive information; only mild trimming would be possible.

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?

No output schema or annotations exist, so the description must stand alone, and it covers scope, cost, depth limits, and known blind spots well. The main gap is that it doesn't describe the response shape or how 'unable to establish' results are surfaced.

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 baseline is 3 and the schema already documents chain, ticker, creator, and subscription_token. The description adds interpretive context (ticker collision check, creator as the connected wallet), but no per-parameter syntax or defaults beyond what the schema provides.

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?

Opens with a specific verb and resource ('Screen who is asking to launch') and immediately scopes it against the launch workflow. It enumerates the concrete checks (OFAC SDN, funding chain to depth 33, mixer contact, dusting, control clusters) so the agent knows exactly what the tool does, and it clearly separates itself from post_launch_screening by noting it reports on the party, not the launch.

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?

Gives clear timing context ('before you deploy anything for them') and contrasts itself with sibling wallet_verification by stating it includes the full verification rather than a summary. It does not name alternative tools for the post-launch case or explicitly state when-not-to-use, so it stops short of full routing guidance.

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

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

With no annotations provided, the description carries the full burden and does well: it discloses the per-call cost ($1.00 USDC via x402), the optional subscription token path to quota, and the output (ZKP with verification ID and URL). It does not mention rate limits or data storage details, but the core behaviors are covered.

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

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

The description is two sentences and front-loads the core purpose. It packs cost, payment method, output artifacts, and privacy guarantee without repetition 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?

With only two parameters, no output schema, and no annotations, the description covers the essential return values and cost model. It is complete for basic invocation, though it could briefly mention what the verification ID/URL are for or how it differs from sibling verification tools to be fully self-contained.

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

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

The input schema covers both parameters with descriptions, so the baseline is 3. The description adds meaningful semantics by explaining cpdv_data as 'text integrity' validation and clarifying that the tool proves facts without revealing the data, which elaborates on the schema's terse 'Data (e.g., Test Data)' example.

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

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

Description uses a specific verb 'prove' and clearly states the resource: a fact about private data, validated as text integrity, with a zero-knowledge proof output. This distinguishes it from sibling verification tools by focusing on private data rather than tokens, media, or wallets.

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 opening phrase 'Prove a fact about private data without revealing the data' provides clear context for when this tool should be used. However, it does not explicitly name alternative tools or state when not to use it, so it stops short of full exclusionary guidance.

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

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

No annotations are provided, so the description carries the full burden. It discloses the cost ($1.00 per call, paid in USDC over x402), the output (record ID and decrypt URL), and the core function. This is adequate for a simple encryption tool, though it does not elaborate on data storage or limitations.

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

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

The description is three short sentences that efficiently convey purpose, use case, and cost. There is no filler or redundant information, and key details are front-loaded.

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?

This is a straightforward paid encryption service. The description explains what it does, when to use it, what it returns, and its price, making it sufficiently complete for an agent to decide on invocation. No output schema exists, but the description compensates with return-value details.

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

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

The input schema covers both parameters (cqcv_data and subscription_token) with descriptions, achieving 100% coverage. The description adds no additional parameter-specific details, but the schema already provides the needed 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 tool encrypts text using quantum-resistant (post-quantum) cryptography, specifying the use case of protecting secrets that must outlast classical encryption. It distinguishes itself from sibling verification tools by focusing on encryption and returning a decrypt URL.

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 phrase 'for secrets that must outlast classical encryption' provides clear context for when to use this tool. It does not explicitly mention alternatives or exclusions, but the use case is well-delineated.

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

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

No annotations are provided, so the description carries the full burden. It mentions 'live feed' and 'Free,' which give some context, but it does not disclose limitations, data freshness, rate limits, or whether the operation is read-only. The behavioral traits are only minimally addressed, and no safety or side-effect information is provided.

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 sentence that immediately states the core function and key output information. It is front-loaded with 'Recent real-world web3 exploits' and includes no filler or redundant details, 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?

There is no output schema, so the description must explain return values, which it does by listing loss amounts, attack vectors, and the Cybercentry service. It also provides context via 'live feed' and 'Free.' It does not detail output format or error handling, but for a simple feed tool with a limit parameter, this is largely complete.

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 already fully documents the single 'limit' parameter with a clear description and default value. The tool description adds no further semantic detail about how limit affects results. With 100% schema coverage, the description does not need to compensate, and the baseline 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 returns 'recent real-world web3 exploits' with specific output fields (loss amounts, attack vectors, Cybercentry service). This is a specific verb+resource and clearly distinguishes it from the sibling verification tools, which focus on security verifications rather than exploit feeds.

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 a use case for accessing current exploit data via the live feed, but it does not explicitly state when to use this tool over alternatives or mention exclusions. The sibling tools are all verification-related, so the context suggests this is for retriving exploit intelligence, but explicit guidance is missing.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It discloses cost and payment method ('Costs $1.00 per call, paid in USDC over x402') and mentions output ('findings with a clear risk level'). But it does not mention whether the code is sent externally, whether the action is read-only, or any authorization/privacy implications, which are significant for a security auditing 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 two concise sentences that immediately state the purpose, output, and cost. Every sentence adds value and there is no wasted wording or repetition of the title or schema fields.

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

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

For a simple tool with one required parameter and no output schema, the description is largely complete: it tells the agent what to pass, what the tool will do, and what to expect back. The missing details are around output structure and potential input limitations, but the current level is enough for an agent to invoke the tool confidently.

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. The description does add meaningful context by explaining the cost model and the purpose of the tool, which indirectly supports the 'solidity_code' parameter, but it does not add new syntax or detailed parameter-level semantics beyond the schema.

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 a specific action ('Audit Solidity smart contract source for vulnerabilities') and identifies the unique resource (Solidity source code). It also distinguishes from sibling token verification tools by focusing on general Solidity code rather than a specific token standard or blockchain.

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 phrase 'before you deploy or call it' provides clear timing/context for when to use this tool. However, it does not explicitly state when not to use it or name alternative sibling tools, so it falls just 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 burden of disclosing behavioral traits. It mentions the per-call cost, payment method (USDC via x402), and the 33-chain scope. However, it does not disclose the output format, potential side effects (e.g., whether it modifies anything), or any limitations or error conditions. This is a reasonable but not exhaustive disclosure.

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 at two sentences, with the core purpose front-loaded and the cost/payment details placed after. Every word adds information, and there is no redundant phrasing or filler.

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 that there is no output schema, the description could benefit from explaining what the result looks like (e.g., risk score, boolean flag). However, for a screening tool with one required parameter, the description covers the purpose, scope, and cost adequately. It does not explain prerequisites or limitations, but these are not critical for a simple call.

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. The description adds value by stating the cost per call, which is directly relevant to the subscription_token parameter's purpose (using plan quota instead of paying). This goes slightly beyond the schema's basic descriptions, providing operational context for parameter selection.

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 verb (screen), resource (wallet address), and specific actions (OFAC SDN sanctions, risk scoring, suspicious-activity detection) across a defined scope (33 EVM chains). This distinguishes it from sibling verification tools, which target different assets (tokens, media, etc.).

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 gives explicit context for when to use the tool ('Check a counterparty before you transact with it') and mentions the cost and payment method, which is an important operational consideration. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for an agent to select it appropriately.

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 present, so the description carries the full burden. It discloses the cost ($1.00 per call, paid in USDC over x402), which is a key behavioral trait beyond the schema. However, it does not mention whether the scan is read-only, what data is sent to the service, or the format of the returned results.

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

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

The description is two sentences with no filler. The first sentence covers purpose and use case, the second conveys cost and payment method. Every word earns its place.

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

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

There is no output schema, so the description should explain what kind of result the agent can expect. It doesn't mention the output format, severity levels, or scope of OWASP checks. While the use case and cost are covered, the missing output information leaves the agent under-informed.

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% coverage with both parameters described ('target_url' and 'subscription_token'). The description adds context that target_url refers to a website or dApp frontend, but this is already inferable from the tool's purpose. Baseline 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 with a specific verb ('Scan') and resource ('a website or dApp frontend'), and notes it uses OWASP checks. It distinguishes itself from sibling verification tools by targeting web/dApp frontends rather than tokens, wallets, or media.

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 an explicit use case: 'before connecting a wallet to it or trusting it with user data.' This tells when to use the tool, though it doesn't explicitly mention alternatives or 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.