100pro-token-risk

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

Beyond the annotations, the description discloses the payment mechanism, the 402 challenge-and-retry flow, batch pricing, no-account/no-API-key requirement, and explicitly states it 'never signs, transfers, or approves anything on the caller's behalf.' These are meaningful behavioral details not carried by the 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 dense but every sentence carries important operational or behavioral information. It front-loads the core purpose, then covers outputs, inputs, pricing, and safety in a compact, logically ordered block with no 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 the tool's complexity, the description covers purpose, output format, input constraints, supported chains, pricing, authentication model, and read-only guarantees. The presence of an output schema means return-value details are already structured, so nothing needed for correct invocation is missing.

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 description does not need to add parameter meaning; the schema already documents chain defaults and address format. The description does repeat batch semantics but adds no significant new parameter-level information 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?

The description clearly states the tool performs 'Contract-level due diligence for an EVM contract address' and enumerates specific checks (verification route, bytecode match, proxy, deployer, capability scan). This is a specific verb-plus-resource statement that naturally distinguishes it from the token and wallet sibling tools.

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

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

The description establishes a clear context: use for EVM contract source verification and due diligence, including conditions like batch limits and payment. It does not explicitly name the sibling tools or state when not to use them, but the contract focus is unambiguous enough to guide selection.

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

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description goes well beyond this: it explicitly states 'it never signs, transfers, or approves anything on the caller's behalf', discloses the payment model (pricing, x402 v2, no account/API key), explains the HTTP 402 flow with payment challenge, and notes the batch limit of 5. No contradiction with annotations; it adds critical operational 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 moderately long but every sentence serves a purpose: purpose, output format, batching, pricing, payment flow, and read-only guarantee. It is front-loaded with the core purpose and returns, and avoids redundancy. The only minor inefficiency is the length, but it packs essential details without 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 (multi-chain, payment handling, batching, output report), the description is remarkably complete. It covers chain inference, batch limits, exact pricing, payment challenge behavior, and the content of the markdown report including the Verdict. An agent has everything needed to call it correctly and interpret the result. The output schema is separately provided, so not repeating its content is appropriate.

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% for both parameters, and the description enriches them: it explains the chain inference default (0x… → Base, base58 → Solana), gives concrete examples for both token formats, and clarifies the comma-separated batching syntax for up to 5 addresses. This goes beyond the schema's built-in descriptions, providing practical guidance for constructing valid inputs.

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

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

The description opens with a specific verb phrase 'Pre-trade risk screen' and names the exact resource type (EVM token contract or Solana SPL mint) plus the supported chains. It enumerates the checks performed (honeypot, tax, LP-lock, authorities, etc.) and a final Verdict, which clearly distinguishes it from the sibling tools (contract_source_check and wallet_risk_screen) by focusing on token-specific risk analysis.

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 makes the intended use case explicit ('Pre-trade risk screen') and details the batching and payment flow. It doesn't explicitly name sibling tools or state 'when not to use', but the purpose is unambiguous and the scope (token contract/mint risk) naturally separates it from contract source or wallet risk screens. It also explains the optional chain parameter and when to set it explicitly, aiding correct invocation.

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?

Beyond the annotations, the description reveals important behaviors: it is read-only, never signs/transfers/approves, returns markdown with a Verdict, and handles unpaid calls with HTTP 402 with a payment challenge and _meta retry. This goes well beyond the default annotation hints and gives the agent accurate expectations for real-world 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 information-dense but well organized: purpose and outputs first, then limits, pricing, payment flow, and a final read-only assurance. Every sentence adds unique value, and key constraints are front-loaded. No filler or repetition.

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 tool with multiple chains, batching, payments, and output format, the description covers all necessary operational aspects: what it returns, how to pay, what to do on 402, and what side effects it will not have. Given the output schema exists, the absence of a detailed return schema in prose is not a gap.

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

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

The input schema already covers address format, batching up to 5 addresses, chain enum, and Base default. The description adds practical meaning tied to parameters, such as batching up to 5 comma-separated addresses, pricing per batch size, and the x402 payment context. This supplements the schema without redundancy, earning a score above the baseline 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?

Description opens with 'Wallet-level due diligence for an EVM address' and enumerates specific checks, making the purpose explicit and differentiating it from the sibling tools (contract_source_check, token_risk_screen) by scope. It clearly names the resource type and what kind of output is produced.

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 concrete usage context: wallet-level screening, supported chains, batch limits, and payment expectations. It does not explicitly mention the sibling tools for contrast, but 'wallet-level' plus the listed contents makes the intended use clear. No exclusion criteria are provided, but none are critical given the strong contextual signal.

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