Second Opinion

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

With no annotations, the description carries the burden. It discloses cost ($0.75), latency (~90s), the three lenses, and the payment-quote behavior. No destructive actions are implied, but authentication details for the payment step are inferred.

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, each with a clear purpose: first states the mechanism, second gives usage scenario, third explains payment behavior. No redundancy, front-loaded with key 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?

The description covers the tool's purpose, when to use, and payment behavior. However, there is no output schema, and the description does not detail the return format (e.g., vote results, quote object). This leaves some ambiguity for the agent.

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%, but the description adds significant value: it explains the purpose of 'claim' (plainly stated), 'context' (why it matters), and crucially that 'payment' can be omitted to get a quote. This clarifies behavior 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 uses three independent adversarial verifiers attacking through evidence, logic, and currency and voting. It distinguishes from siblings by explicitly recommending it for high-stakes claims where a single check is insufficient.

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 specifies when to use (high-stakes or contested claims) and provides guidance on omitting payment for a quote. It implies alternatives like a single check but does not explicitly name sibling tools.

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

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It mentions that the tool is free, provides current tiers and exact payment requirements, which is useful context. However, it does not explicitly state that this is a read-only operation or note any limitations (e.g., data freshness, no on-chain execution). The description is adequate but could be more transparent about the tool's non-mutating nature and potential 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 sentences, front-loaded with 'FREE' and the key output, and every word earns its place. It is concise, structured with a dash to list the rails, and immediately conveys the purpose and usage 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?

This is a simple zero-parameter pricing lookup tool with no output schema and no annotations. The description covers its purpose, the specific rails, the information provided, and when to use it. It is complete for the tool's complexity, leaving no significant gaps.

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

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

The tool has zero parameters, so there is no schema to interpret. The description adds meaning by explaining what the tool returns (tiers, prices, payment requirements) and the scope (every rail). This exceeds the baseline for a no-parameter tool, as it clarifies the output content and intended use.

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 does: it provides current tiers, prices, and exact on-chain payment requirements for every supported rail (Algorand, Base, Polygon, Solana). This is a specific resource with a clear purpose, and it is distinct from sibling tools like second_opinion_verify or second_opinion_result, which handle verification or results.

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 explicitly says 'Use this to pre-build a payment, or to discover what a verification will cost before committing,' which gives clear context for when to use the tool. It does not explicitly mention alternatives or exclusions, but the usage guidance is strong and implies this is the pricing lookup tool among the siblings.

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

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

With no annotations provided, the description carries full behavioral disclosure. It reveals cost ($0.02), latency (~20s), the lack of web research, the exact outcome categories (refuted/supported/inconclusive), calibrated confidence, and the no-auth, quote-only behavior when no payment is supplied.

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 compact—three sentences—and every clause delivers distinct value: purpose, limitations, pricing, latency, use cases, return outcomes, escalation path, and payment-quote behavior. There is no filler or redundancy.

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

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

For a tool with no annotations and no output schema, the description covers all critical aspects: what it does, when to use it, what it returns, how it handles edge cases (payment omitted), and how it relates to a sibling tool. No significant operational gaps remain.

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 has 100% coverage with clear descriptions for all three parameters. The description adds useful context about the payment parameter's quote behavior, but it does not significantly deepen the semantics of the claim or context parameters beyond what the schema already states.

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 and resource: 'Independent reasoning-only check of a claim.' It clearly distinguishes from sibling tools by explicitly naming second_opinion_verify for current-world research, while this tool handles logic, internal consistency, and stable knowledge.

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?

It explicitly tells when to use the tool: 'Use for logic, internal consistency, and stable established knowledge (definitions, architectures, history, maths).' It also names the alternative pathway by saying it 'escalates to second_opinion_verify when the claim needs current-world research.'

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 full burden. It discloses that polling is free and returns status and full verdict when done. It does not cover rate limits, auth, or whether the result is cached, but is adequate for a simple poll.

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 sentences with key information front-loaded: what it does (fetch verdict), key behavioral prompts (polling free, paid already), and return format (status + verdict). Every sentence is essential; no wasted words.

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

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

Given no output schema, the description adequately explains return values (status and verdict). With one parameter well-documented in schema, the description is sufficient. It could mention polling interval advice or how to interpret statuses, but not a major 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% (job_id documented in schema). The tool description adds no additional parameter meaning beyond what the schema provides, so baseline score of 3 is appropriate.

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

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

The description clearly states it fetches the verdict for a paid async job and returns status and verdict. It distinguishes from siblings by implying this is the polling endpoint after a paid verification, but does not explicitly differentiate.

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 mentions polling is free and verdict is paid for, implying usage after a paid verification. However, it does not explicitly state when to use this tool versus alternatives like second_opinion_verify or second_opinion_quick.

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?

Despite no annotations, the description discloses key behaviors: free trial, no wallet/payment required, 3/day limit, global daily cap, unsigned verdict, and comparison to paid tiers. It does not detail error handling or response format, but covers the main behavioral traits for a trial 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?

Three sentences, front-loaded with 'FREE TRIAL', and no redundant information. Every sentence adds value: purpose, limits, comparison, and guidance.

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 trial tool, the description adequately covers the context: what it does, its limitations, and how it differs from paid versions. It does not describe output format or error behavior, but given the tool's simplicity and lack of output schema, this is acceptable.

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 both parameters (claim, context), so the baseline is 3. The tool description adds the trial-specific limit of 500 chars for claim, but otherwise does not enrich parameter meaning 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 it is a free trial tool providing the same reasoning-only check as second_opinion_quick, with specific limits and without the paid features (Ed25519 receipt, live web research). It effectively distinguishes itself from siblings.

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?

Explicitly says 'use the paid tools for real work', indicating this is for trial purposes. Also notes it is the same as second_opinion_quick, guiding when to use this versus siblings.

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?

Discloses the adversarial verification process, live web research, cost, timing, and the behavior of returning a quote without a payment argument. Annotations are absent, so the description carries the burden well.

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 four sentences long, front-loads the core concept, and includes cost and timing. Every sentence adds necessary information with no redundancy.

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

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

Covers the tool's purpose, parameters, workflow, and pricing. Lacks details on the exact format of the returned verdict and error handling, but for a tool with no output schema and good parameter descriptions, it is fairly 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 baseline is 3. The description adds context beyond schema descriptions: explains the purpose of context, the nature of payment as x402 payload, and that claimed_sources will be scrutinized. This adds meaningful value.

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

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

The description clearly states the tool performs independent adversarial verification with live web research, refuting a claim. It distinguishes from siblings by specifying its full verification process versus quick or pricing variants.

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?

Explicitly advises use before irreversible commitments dependent on current-world facts and explains how to obtain a quote without payment. Lacks explicit when-not-to-use or comparisons to siblings.

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