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

With no annotations, the description carries the full burden and does so thoroughly: exact offline match against a bundled dated snapshot, EVM/Base chain applicability, the three result buckets (listed, not listed, invalid), and the source/date returned. It also discloses critical limits — 'Not listed' is not a compliance clearance, no fund/ownership tracing, and post-snapshot additions are excluded.

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 purpose and trigger before the mechanics and caveats. The three paragraphs are each doing work, though the limitation paragraph is dense and slightly longer than strictly necessary.

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?

Covers what an agent needs to call it correctly and interpret results: scope, chain validity, snapshot basis, return categories, and the boundaries of what 'Not listed' means. An output schema exists, so return-value detail is a bonus rather than a requirement.

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, and the description earns above it by adding chain-scope semantics (Ethereum-format addresses also valid for Base and other EVM chains) that the schema does not convey. Only the 'up to 100' bound is left to 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?

States a specific verb+resource ('Check addresses against the OFAC SDN list') and an explicit scope ('before dealing with them, for example before creating a payment'). The sanctioned-address checking function is clearly distinct from the sibling payment-rule and payment-checking tools, even though siblings aren't named.

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 triggering context ('before dealing with them, for example before creating a payment') and an operational directive ('Do not pay or approve anything involving a listed address; refer it to a human'). It does not explicitly contrast itself with the sibling check_* tools, so it stops short of full when/when-not/alternatives 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, the description carries the full burden and does so well: it discloses the bundled dated OFAC snapshot, the exact set of checks, the fact that unsupported chains return 'hold', the prompt-injection hold behavior on self-claiming text, and the returned decision/flags/explanation/required_actions. The distinction between deterministic checking and model-based checking is 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?

Front-loaded with the purpose and the check list, then the untrusted_text and chain caveats, then the return shape. Every sentence carries information, though the parenthetical examples and multi-paragraph layout make it longer than strictly minimal.

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 six-parameter deterministic screening tool with an output schema, the description covers the supported chains, the unsupported-chain behavior, the injection-hold rule, the optional depeg input, and the action gating. Nothing an agent needs in order to call and act on it correctly 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 coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the schema: peg_deviation_pct is defined as USDC's percent deviation from $1.00 with an example and the note that omitting it skips the depeg check, and untrusted_text is given explicit pass/do-not-pass semantics. Only the four core address/amount params are left entirely to 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?

States a specific verb and resource ('Instant deterministic checks for a USDC payment') and enumerates exactly what is checked (OFAC SDN, address validity, self-transfers, zero address, amount ceiling, depeg). The phrase 'No model or GPU needed' implicitly separates it from the sibling check_payment_with_model, so an agent can route without opening a schema.

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 context ('before sending it'), an explicit gating rule ('Only send the payment if decision is approve'), and strong negative guidance for untrusted_text ('Never pass the results of your own verification tools there'). It does not explicitly name the sibling tools it should be chosen over (e.g. check_payment_with_model or check_x402_payment), which keeps it 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, the description carries the full burden and does so well: it names the model dependency, the training-format arguments, the fallback to 'hold' on unavailability or off-schema output, and the prompt-injection guard that forces 'hold' before the model runs. These are non-obvious behavioral traits an agent cannot infer from the schema.

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

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

Front-loads the purpose and key dependency, then uses an indented argument list. Every line is substantive, though the argument enumeration partially duplicates the schema and could be tighter.

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?

Though an output schema exists and explains return values, the description adds essential context: the fallback behavior, the injection guard, and the required local model. Given the overt security sensitivity (untrusted payload, injection handling), a bit more on trust boundary or expected tool_results shape would help, but it 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?

Schema description coverage is 100%, so the schema already documents all four parameters. The description restates the model's training-format argument names and semantics, adding marginal framing (payload treated as untrusted, tool_results are pre-run) but no syntax or format detail 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?

States a specific verb (risk review), resource (stablecoin payment), and names the specific model doing the reasoning (SRA-RiskGate-4B). It is distinguishable from siblings like check_payment_rules and check_x402_payment by being explicitly model-based, though it doesn't directly contrast itself with them.

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 a key gating instruction ('Only proceed if decision is approve') and a prerequisite (model must run locally), which is useful. However it never explicitly says when to use this versus the sibling tools check_payment_rules or check_x402_payment, leaving the primary routing decision to inference.

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 behavioral burden and does so well: OFAC SDN rejection against a bundled dated snapshot, hard rejection of anything that is not USDC on the three named chains, and the note that self-asserted claims are 'held'. It does not describe rate limits, latency, or failure behavior on malformed input.

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-loads the imperative and decision rule, then groups the field mapping in one dense paragraph. Every sentence carries information, though the field enumeration overlaps with what the schema already states.

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?

An output schema exists, so the description needn't explain return shape, and it correctly only references 'decision is "approve"'. Scope limits, untrusted-text handling, and the optional depeg check are all covered; nothing an agent needs to call this safely 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% and the schema already documents every field, including the 6-decimal USDC example and 'Never your own verification results'. The description restates the same semantics (CAIP-2 formats, smallest-unit string, payer is your own wallet) with little that is not already in the schema, so the baseline 3 applies.

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 ('Check an x402 payment requirement') and pins the timing ('BEFORE signing it'), which is the agent's key decision point. It also declares scope (USDC on Ethereum, Base, Base Sepolia) and rejection rules, but never names or distinguishes itself from siblings like check_payment_rules or check_address_sanctions.

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 a clear operative rule ('Only sign and pay if decision is "approve"') plus precondition timing ('BEFORE signing it') and per-parameter guidance ('Omit if unknown; the depeg check is then skipped and reported'). It stops short of explicitly routing the agent away from the sibling checking tools.

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