chainverdict

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the description is not required to restate the safety profile. It adds the price and that the data reflects the 'Latest' block, which signals a changing result, but it does not disclose response format or units. This is acceptable but not richly informative.

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 compact line that front-loads the returned values and ends with the pricing call-out. Every token earns its place, and there is no filler for a tool this simple.

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

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

For a zero-parameter, read-only lookup, the listed fields are mostly sufficient, but the description omits the network context ('Base' appears only in the title), the timestamp unit, and the gas utilization format. Since there is no output schema, a bit more detail about the response would round it out.

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 and schema coverage is 100%, so the baseline of 4 applies. The description does not need to explain parameters because there are none, and it correctly implies a no-input invocation.

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 enumerates the tool's output: 'Latest block number, timestamp, tx count, gas utilization.' This makes the resource and purpose obvious even without an explicit verb. It does not, however, explicitly differentiate itself from sibling data_* tools by naming any alternative.

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?

There is no guidance about when to use this tool versus siblings like data_gas or data_token_supply, and no exclusions or conditions of use. The only extra contextual note is the price, '$0.001 per call,' which implies a cost consideration but not a usage scenario.

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 establish read-only, idempotent, open-world, and non-destructive behavior. The description usefully adds that data is live, includes an estimated transfer cost, and that each call costs $0.002, which is additional behavioral context beyond 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 concise and front-loaded, using one sentence to state the core purpose and a short second sentence for pricing. Every word adds value, with no repetition of the title or schema.

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 there are no parameters, a rich set of annotations, and no output schema, the description adequately covers what data is returned, the network (Base), and the cost. Nothing essential is missing for an agent to decide to call and interpret 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 tool takes no parameters, so schema description coverage is trivially 100%. With zero parameters, the description does not need to explain parameter semantics, and it appropriately focuses on what the returned data will include.

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 what the tool provides: live Base gas conditions, including base fee, priority fees, congestion, and estimated transfer cost. It distinguishes this tool from sibling data tools by focusing specifically on gas on Base, although it lacks an explicit action verb like 'get' or 'fetch.'

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 context for use is implied: call this tool when you need current gas information on Base. However, the description does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or conditions where another tool would be preferable.

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 read-only, idempotent, and non-destructive behavior, so the description's main behavioral contribution is the explicit per-call cost of $0.004 and the canonical token scope. This adds useful transparency beyond the annotations without contradicting them.

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 short, information-dense segments: one describing exactly what balances are returned and one disclosing cost. There is no redundancy, filler, or repetition of the title.

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 one-parameter read-only balance tool, the description together with the schema and annotations provides enough for an agent to invoke it correctly. The absence of an output schema means return formatting is not fully specified, but the high-level return content is clearly communicated.

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 single address parameter is already fully described in the input schema, including format and character length, so schema coverage is 100%. The description adds context about return content but does not meaningfully extend the parameter semantics beyond what the schema already 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 identifies the tool as returning ETH and canonical token balances for a specific address, which is specific enough to distinguish it from token_activity and token_supply siblings. However, it does not clearly distinguish itself from wallet_dossier, which could plausibly also include portfolio-style balance information.

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

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

The description implies usage for balance lookups on Base and lists exactly which tokens are covered, so an agent can infer when to call it. It does not provide explicit 'use this when' guidance or mention alternatives, leaving selection partially 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?

Annotations already cover read-only, idempotent, and non-destructive behavior, so the description does not need to repeat those. The description adds useful context: the returned data categories and the per-call cost ($0.005). However, it does not clarify return format, volume denomination, or how 'recent' relates to the blocks parameter, which would be valuable since no output schema exists.

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?

Two concise sentences with no filler. The first sentence front-loads the tool's output, and the second provides cost transparency. 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?

For a simple read-only tool with two parameters and rich annotations, the description is largely complete. It names the key output metrics, and the schema covers the parameters. Minor gaps remain: no explicit statement that 'activity level' is derived from the other metrics and no mention of output shape, but these are not critical for a successful 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%, with both parameters ('address' and 'blocks') explained in the schema. The description adds no additional parameter-level semantics, but that is acceptable given the schema carries the full burden. Baseline 3 applies because the schema fully documents the parameters.

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

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

The description clearly identifies the resource ('Token transfer activity') and the specific data points it provides (transfer count, volume, unique senders/receivers, activity level). It lacks an explicit verb like 'get' or 'retrieve', but the intent is unambiguous. It is distinguishable from siblings like data_token_supply, which focuses on supply, and token_verdict, which likely focuses on 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 gives no guidance on when to use this tool versus the many sibling tools (e.g., data_token_supply, token_verdict, data_portfolio). There are no explicit conditions, exclusions, or alternative suggestions. Usage is only implied by the name and description, which is weak given the large sibling set.

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 this a read-only, idempotent, non-destructive operation, so the description does not need to repeat safety traits. It adds only the $0.003 per call pricing, but it does not disclose call behavior such as output format, network edge cases, or any data freshness caveats.

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 short sentences with no redundancy. The core metric set is front-loaded, and the pricing note is separated and useful.

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 one-parameter read-only tool, the description covers the tool's purpose, the key returned values, and cost, while the schema documents the address. A minor gap is that it does not explicitly describe the response container or edge cases, but the tool is simple enough that it remains sufficiently 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 provides 100% coverage for the single address parameter, including its format on Base. The description adds no extra parameter semantics, so the baseline 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 identifies the resource (ERC-20 token supply data on Base) and the specific metrics returned (total, circulating, burned supply and burn percentage). It is distinct in content, but it does not explicitly differentiate itself from sibling data_* tools, so it stops short of a 5.

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

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

The description implies the tool should be used when an agent needs ERC-20 supply and burn metrics on Base. However, it provides no explicit when-not-to-use guidance and does not name any alternative sibling tools, so the routing decision is left largely 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?

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds the useful operational detail of cost per call. However, it does not disclose behavior on invalid HTML, tag stripping specifics, or size limits, so the description carries only modest behavioral value beyond 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?

One focused sentence captures the transformation, and the pricing note is brief and useful operational context. There is no fluff, and the core purpose is 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?

With one fully documented required parameter, rich annotations, and a self-evident conversion, the description is nearly complete. The only notable omission is explicit confirmation of the return type, though 'to clean Markdown' strongly implies it.

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%: the single 'html' parameter is already described as a raw HTML string for full document or fragment. The description merely restates that concept, adding no new semantic detail about formats, encoding, or accepted variants.

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 ('Convert'), a precise input resource ('raw HTML'), and output ('clean Markdown'). It is immediately distinguishable from the sibling tools, none of which describe an HTML-to-Markdown conversion.

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?

While it does not explicitly say 'use this instead of X', the single-purpose instruction makes the intended use case obvious: whenever raw HTML must become Markdown. There are no close sibling alternatives that compete with this behavior, so the lack of exclusion phrasing is a minor gap.

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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds helpful context by stating the tool is free and that it explains payment methods, which aligns with the annotations and adds mild value beyond them.

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, front-loaded with 'Free,' and packs all essential information without any filler. Every clause contributes meaning: pricing, protocol, network details, and tool-specific costs.

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

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

For a zero-parameter informational tool with read-only, idempotent, non-destructive annotations, the description covers all that an agent needs: what it is, what it contains, and why it exists. No return schema is necessary given the explanatory nature of the output.

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 the schema requires no documentation. The description still adds relevant context about what the tool will do, which is sufficient for an agent to invoke it correctly without any input.

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 names a specific verb ('Explains how to call the paid tools'), a clear resource (paid tools on this server), and enumerates the exact content covered (x402 protocol, network/asset, settlement address, price). This clearly distinguishes it from sibling tools like verify_payment or data_gas.

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 when to use the tool: whenever an agent needs to understand how to pay for paid tools on this server. It does not explicitly state when not to use it or name alternatives, but the context is straightforward given the empty schema and informational nature.

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 read-only, idempotent, non-destructive behavior. The description adds that this is a live DNS check and that it costs money per call, which are useful behavioral details beyond the annotations. It does not contradict the annotation's safety profile.

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 concise sentence plus a cost note. Every word earns its place, and the core purpose is 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?

With only two parameters, one required, and rich read-only annotations, this definition is adequate for an agent to call correctly. There is no output schema, and the description does not spell out the return format, but the title and purpose make the expected DNS-record results inferable.

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 both 'domain' and 'selector' clearly. The description adds context about DNS records but does not add meaningfully beyond the schema's parameter definitions.

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 uses a specific verb and resource: 'Live DNS check of a domain's email authentication records,' and the title clarifies the scope to SPF/DMARC/DKIM. This makes it easy to distinguish from security_tls and security_typosquat without opening schemas.

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 checking email authentication/spoofing posture, which is clear context, but it does not explicitly say when to prefer this over sibling tools or when not to use it. There is no misleading guidance, just no explicit 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?

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds value by disclosing that the tool performs a live network handshake (real-time external state dependency) and that each call costs $0.01 — useful behavioral context beyond 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?

A single, dense sentence that front-loads the core action ('Live TLS handshake') followed by concrete outputs and pricing. No wasted words; every element 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?

For a one-parameter tool with rich annotations and no output schema, the description is complete enough: it lists the key returned data (validity, issuer, expiry countdown) and notes the cost. It does not describe error handling or exact response structure, but these are minor given the simplicity of 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?

Schema description coverage is 100% for the single parameter 'domain', which already specifies a hostname without scheme and port 443. The description does not add meaning beyond the schema; it only references the domain implicitly through the handshake context. Baseline 3 applies because the schema carries the full parameter load.

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 states a specific action ('Live TLS handshake') and the exact outputs (cert validity, issuer, expiry countdown). The resource is clear — a TLS certificate check — and the tool is easily distinguished from siblings like security_email or security_typosquat.

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 the use case: whenever a live TLS certificate check is needed. However, it does not explicitly state when to use this tool over alternatives, nor does it mention exclusions or route to siblings like security_email for different security checks.

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 establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context beyond these by disclosing the cost ($0.005 per call) and the algorithmic approach (homoglyph and edit-distance matching). This helps the agent understand the tool's cost profile and how it flags look-alikes.

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

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

The description is two concise sentences with no filler. The primary function is front-loaded, and the pricing note is included as a separate short sentence. 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?

For a simple two-parameter tool with one required parameter, full schema coverage, and safety annotations, the description covers purpose, method, cost, and parameter roles. The only gap is that it does not describe the return format, but with no output schema required, this is a minor omission in an otherwise complete definition.

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% because both 'domain' and 'brands' have clear descriptions. The description's mention of 'known brands' and the built-in set aligns with the brands parameter but adds no new syntax, defaults, or format beyond what the schema already provides. Thus it meets the baseline but does not exceed it.

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 uses a specific verb 'Flags' with a clearly defined resource: homoglyph and edit-distance look-alikes of known brands. The examples (c0inbase, b1nance) and the title 'Typosquat / look-alike domain check' make the tool's purpose unambiguous and distinguish it from siblings like security_email and security_tls.

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?

No explicit guidance is provided on when to use this tool versus alternatives. The description implies it is for checking whether a domain impersonates a brand, but it does not state when to prefer it over other security tools or when not to use it. This leaves the agent to infer the appropriate context.

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=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds only the pricing note ($0.002 per call) and does not disclose the output format or any side effects. Given the annotations cover the main behavioral traits, a 3 is appropriate—it adds pricing context but nothing about the result structure.

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 one short sentence plus a cost note. It is front-loaded with the core action and granularity, and every word earns its place. There is 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?

The tool lacks an output schema, so the description should explain what the diff result looks like (e.g., unified diff, structured list of changes). It does not, and also omits any guidance on interpreting the output or handling edge cases. For a tool with three parameters and no output schema, this is a significant 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?

Schema description coverage is 100%: each parameter (a, b, mode) has a description. The tool description merely echoes the granularity options already in the enum but adds no new semantic detail. With full schema coverage, the baseline is 3, and the description provides no additional value.

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

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

The description states a specific verb ('Diff') and resource ('two texts'), and also names the granularity options (lines/words/chars), which clearly distinguishes it from the unrelated siblings. It is immediately obvious what this tool does.

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?

There is no guidance on when to use this tool versus any alternative, and no exclusions or prerequisites. While the purpose is self-evident for a diff operation, the description fails to provide context about what input it expects (e.g., plain text vs. formatted) or when a different tool might be more appropriate.

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

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

Annotations already declare the tool read-only, open-world, and idempotent. The description goes beyond this by revealing the heuristic nature of the verdict, the factors examined, and the $0.01 per call cost, which is useful behavioral context that the annotations do not provide.

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, information-dense sentence that front-loads the main outcome and then adds methodology, output scale, and cost. Every clause earns its place, with no redundant 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?

For a single-parameter tool with strong safety annotations, the description covers what the tool checks, the verdict scale, and the pricing implication. Without an output schema, it briefly summarizes the return values enough for an agent to call it, though it stops short of giving exact output shape or sibling differentiation.

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 single parameter, address, is fully documented in the schema with format and chain constraints, so schema coverage is 100%. The description restates 'on Base' but adds no new parameter semantics or constraints beyond what the schema already provides, so the 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 names a specific deliverable — 'Heuristic ERC-20 safety verdict' — and the target chain, Base. It also lists concrete outputs such as bytecode risk capabilities, ownership, metadata, a 0-100 score, and hold/caution/avoid categories, which clearly distinguishes it from siblings like verify_token or data_token_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 purpose implies when to use it: when an ERC-20 token safety assessment on Base is needed. However, it does not explicitly say when to prefer this over siblings such as verify_token, nor does it provide exclusion criteria or when-not-to-use 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?

Annotations already disclose readOnlyHint, idempotentHint, and destructiveHint, so the description needs only to add context. It adds pricing per call and mentions decomposition, but does not explain what the decomposition returns or how validation results are reported. No contradiction with 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?

Two concise sentences deliver the core purpose first and the cost second, with no filler or redundant restatement. Every sentence 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?

For a simple read-only, one-parameter tool, the description plus schema is almost complete: the required input is fully documented and annotations cover safety. The only notable gap is the absence of an output schema and any description of the return shape, but this does not block correct invocation.

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 covers 100% of the single parameter, including format, length, and examples. The description repeats this information without adding further semantic detail such as validation rules, country extraction, or error behavior, so it does not meaningfully extend 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 states the specific verb 'validate' and the resource 'BIC/SWIFT', and adds 'decomposition' as a secondary behavior. This is enough to distinguish it from sibling validators such as validate_iban or validate_isin based on the target code type.

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 no guidance on when to use this tool versus alternatives, despite a large sibling family of validators. It does not mention exclusions, prerequisites, or preferred contexts, so the agent must infer usage from the tool name alone.

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

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

Annotations already declare readOnly, idempotent, non-destructive behavior. The description adds useful behavioral context beyond the annotations: the exact validation algorithm and a $0.001 per-call cost, which an agent needs to know before invoking. No contradiction with annotations exists.

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?

Two short sentences contain zero filler. The core validation logic is front-loaded, followed immediately by the essential cost warning. 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?

For a simple single-parameter validator, the description covers the validation logic, cost, and parameter requirements. It does not explicitly state the return value or error behavior, and there is no output schema, but the tool's purpose and invocation requirements are sufficiently clear for an agent to select and call it correctly.

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

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

Input schema coverage is 100%, so the schema fully documents the single 'iban' parameter, including that spaces are tolerated. The tool description adds no extra parameter-level detail beyond what the schema already provides, so the baseline score of 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?

The description clearly identifies the resource as IBAN and specifies the validation logic: mod-97 checksum plus country length rules. It distinguishes this from sibling validators like validate_bic and validate_isin by naming the exact check performed, though it lacks an explicit verb like 'validate'.

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?

No guidance is given on when to use this tool versus alternatives. The sibling list includes other validation tools, and the description does not mention exclusions, use cases, or when another validator would be more appropriate.

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

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

Annotations already fully declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered without description help. The description adds value with the $0.001 per-call cost disclosure and confirms the operation is deterministic checksum computation, but it does not mention output or error behavior — a minor gap given the annotation coverage.

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?

Two terse fragments with no filler — purpose is front-loaded and the cost disclosure earns its place. It is appropriately sized for a single-parameter validation tool, though the use of fragments instead of full sentences makes it feel slightly under-specified.

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 tool is simple (one fully documented parameter) and annotations are rich, so the description is mostly adequate. However, with no output schema and no mention of return behavior, an agent cannot tell whether validation returns a boolean, throws on malformed input, or reports errors differently — a meaningful gap for a validation tool with zero output documentation.

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

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

Schema description coverage is 100%; the isin parameter is fully documented with format (12-character), standard (ISO 6166), and an example. With the high-coverage baseline of 3, the description is not required to repeat parameter details; the 'checksum' wording adds only marginal context about how the value is evaluated.

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 'Securities identifier checksum validation' conveys a specific action (checksum validation) and resource (securities identifier/ISIN), and the title adds the ISO 6166 standard. It is unambiguous, though it does not explicitly differentiate this tool from sibling validators like validate_bic, validate_iban, validate_lei, or validate_vat — the distinction relies on the tool name.

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

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

No when-to-use guidance, prerequisites, or alternatives are provided. An agent must infer applicability from the sibling names and the schema's ISIN example rather than from the description, which states only what the tool does, not when to choose it over the other validate_* 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is well-covered. The description adds the cost of '$0.002 per call' and scopes behavior to 'checksum validation,' which communicates that full LEI registry verification is not performed. This is useful contextual information beyond what annotations provide.

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 short, front-loaded sentences with no redundant words. The core purpose ('checksum validation') comes first, followed by the only additional behavioral detail (cost). Every word earns its place, and the structure is 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?

The tool has no output schema, so the description carries the burden of explaining what the caller can expect in return, but it does not specify the return type (e.g., boolean, status object, error behavior). It also omits any note about edge cases, such as what happens with a malformed LEI. For a single-param, read-only tool with annotations, the gaps are moderate but noticeable.

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 'lei' parameter already clearly documents length, format, and an example. The tool description adds no additional parameter-level detail. With full schema coverage, a baseline score of 3 is appropriate, as the description does not need to compensate.

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 identifies the operation as 'checksum validation' and the resource as 'Legal Entity Identifier (ISO 17442)', which is specific and informative. It does not explicitly contrast with sibling validators like validate_iban or validate_isin, but the identifier type alone is sufficient to disambiguate. It falls slightly short of a 5 because it never states that it should be used only for LEI and not other identifiers.

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 that the tool is used when a 20-character LEI needs to be checked, but it gives no explicit guidance on when to choose this tool over validate_bic, validate_iban, validate_isin, or validate_vat. There are no exclusion conditions or mention of prerequisites such as 'only for checksum verification, not registry lookup.' Usage context is implied by the resource name 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?

Annotations already signal read-only, idempotent, non-destructive behavior. The description adds meaningful context by disclosing deterministic checksum support for specific countries and the per-call cost, which goes beyond annotation coverage.

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 dense sentence that front-loads the core purpose and includes useful behavioral and cost information without 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?

For a simple one-parameter validation tool, the description is mostly sufficient: it states the operation, supported countries, and cost. However, there is no output schema and the description does not disclose what the tool returns (e.g., boolean, verdict object, or error), which is a relevant gap for an agent invoking 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?

Schema coverage is 100%, so the vat parameter is already fully described as an EU VAT number with country prefix and examples. The description adds the supported country checksum list but does not materially improve parameter understanding 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 states a specific verb and resource: 'EU VAT format validation.' It is clear the tool validates EU VAT numbers, and the supported checksum details add specificity. However, it does not explicitly distinguish itself from sibling validation tools like validate_iban or validate_bic beyond the VAT resource being 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?

The description clearly implies this tool is for validating EU VAT numbers and lists which country checksums are supported. It lacks explicit exclusions or references to alternative tools, but the context is clear enough for an agent to know when to select it.

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

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, lowering the bar. The description adds value beyond annotations by stating the $0.02 per-call cost and clarifying that the tool decodes transfer-level details rather than simply returning a boolean. Edge cases are not discussed, but the annotation coverage mitigates this.

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?

Two tight sentences: the first front-loads the action, resource, and key outputs, and the second adds the cost signal. No filler, no repetition of schema fields, and every word contributes.

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

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

For a single-parameter read-only tool, the description provides the network (Base), asset type (ERC-20), and expected output categories (amounts, counterparties, confirmations). It does not describe the exact return shape or failure behavior, but the annotations and detailed schema parameter cover the essential invocation requirements.

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

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

Schema coverage is 100%; the txhash property already documents the required format (0x-prefixed, 66 chars). The description does not add additional parameter semantics, so the baseline score of 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?

The description uses a specific verb ('Decode') and clearly identifies the resource: ERC-20 transfers in a Base transaction. It enumerates the key outputs (amounts, counterparties, confirmations), which differentiates it from siblings like payment_info or verify_token by network and asset scope.

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 Base-transaction scope implies when this tool is relevant, but the description gives no explicit when-to-use vs alternatives guidance. An agent must infer the distinction from sibling names rather than being told, for example, when to choose verify_payment over payment_info.

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 disclose read-only, idempotent, and non-destructive behavior. The description adds useful behavioral context: it checks against a canonical list, targets specific assets, and costs $0.005 per call. No contradiction with annotations exists.

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

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

The description is two concise sentences with no fluff. The core purpose is front-loaded in the question, and the pricing detail is the only extra but relevant piece of information.

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

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

For a single-parameter read-only verifier with comprehensive annotations, the description is largely complete. The only minor gap is that it does not explicitly state the return format, though the question format strongly implies a yes/no verification result.

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 query parameter is clearly documented as a contract address or symbol. The description itself adds no further parameter detail, so the baseline score of 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?

The description clearly states the tool verifies whether a token is the canonical USDC/EURC/WETH/cbBTC/USDT on Base, giving a specific resource, network, and asset set. The title 'Canonical token check (Base)' reinforces the scope and distinguishes it from generic token or payment 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 'Anti-phishing for stablecoin payments' provides clear contextual guidance on when to use the tool. It does not explicitly name sibling alternatives or state when not to use it, but the stablecoin-payment context is strong enough for an agent to route correctly.

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 read-only, idempotent, non-destructive behavior, so the bar is lower. The description adds useful context about what the profile includes and the per-call price, though it does not disclose flag semantics, data freshness, or return structure.

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, dense sentence that front-loads the core purpose and lists key output dimensions, ending with the price. There is no redundant or filler content.

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 one-parameter read-only tool with no output schema, the description covers the main use case, the address scope, and the kind of data returned. It stops short of detailing exact response fields or edge cases, but it is reasonably complete for its simplicity.

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 the single address parameter. The description adds no meaning beyond the schema's own description of a Base address, so it receives the baseline score.

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 profiles a Base address and lists concrete outputs: EOA vs contract, balance, activity band, flags. It is distinguishable from siblings through the 'Base address' scope, though it never explicitly names an alternative.

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?

There is no guidance about when to use this tool versus siblings like data_portfolio or token_verdict. The description implies address-level profiling but provides no exclusions, preconditions, or alternative routing.

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