Fidenta Verify

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is clearly communicated. The description adds the 'current period' scoping, which is useful behavioral context, but it does not disclose return format, potential latency, or whether the count might be cached. Given the strong annotation coverage, this level is acceptable.

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, well-structured sentence that immediately conveys the purpose. It is front-loaded with the main action and contains no filler words or redundant 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?

Given the tool's simplicity (no parameters, no output schema, read-only hint), the description is sufficient for an agent to select and invoke it correctly. It clearly communicates what the report returns (remaining count) and the relevant time period, making it complete for this use case.

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?

There are zero parameters, so the description carries no burden to explain parameters. The baseline for 0-parameter tools is 4, and the description accurately describes the output without needing to map parameter syntax or semantics.

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

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

The description clearly states a specific verb ('Report'), a specific resource ('verifications remaining'), and a temporal scope ('current period'). It effectively distinguishes itself from sibling tools like 'verify_claims' or 'top_up', which perform actions rather than provide status 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 when to use this tool (to check remaining quota before or during verification activities), but provides no explicit guidance on when not to use it or which alternatives might be more appropriate. It does not mention sibling tools or contrast with them, so usage context is only implied.

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, and non-destructive. The description adds crucial context: it is free, spends nothing, verifies nothing, and reports cost. This explains the economic behavior beyond what annotations capture, making the agent aware of side effects on credits.

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', and every sentence serves a purpose: what it does, what it doesn't do, and when to use it. There is no wasted language.

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 estimation tool with strong annotations and full schema coverage, the description fully covers what the agent needs: it explains the output (count and cost) and the prerequisite for verify_claims. No output schema is needed since the return values are explicitly stated.

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% and both parameters (url, text) have detailed descriptions in the schema. The tool description does not add new parameter semantics, so the baseline of 3 is appropriate.

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

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

The description states exactly what the tool does: break text into checkable claims and report the count and credit cost. The verb 'break' and the resource 'claims' are specific, and it clearly distinguishes itself from verify_claims by emphasizing it estimates rather than verifies.

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 instructs to 'Always call this before verify_claims' and explains the rationale with cost awareness. It also contrasts with the alternative (verify_claims) and provides condition ('anything longer than a sentence or two').

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 and openWorldHint=false. The description adds useful behavioral context: it does not spend a verification (a cost-related detail) and operates 'on this account.' This goes beyond the annotation hints, indicating a read-only, account-scoped lookup. No contradictions 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?

The description is a single, concise sentence (14 words) that immediately states the purpose and key differentiator ('without spending a verification'). No filler or repetition; 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 lookup tool with one string parameter and no output schema, the description covers the essential context: what it checks, scope (this account), and cost implications. It does not specify the return format, but 'whether' strongly implies a boolean outcome, which is sufficient for this complexity level.

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 0%, so the description must clarify the parameter. The description implies 'claim' is a previously submitted statement whose verification state is being checked, which adds some meaning beyond the plain string name. However, it does not specify format, exactness, or any normalization requirements, leaving room for ambiguity.

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 ('look up') and clearly identifies the resource ('whether a claim has already been verified on this account'). It distinguishes itself from sibling tools by explicitly noting it does not spend a verification, contrasting with verify_claims.

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 'without spending a verification' implies a clear use case: check prior verification status when you want to avoid the cost of verifying. This provides clear context for when to use the tool, though it does not explicitly name alternatives or provide exclusionary guidance.

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

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

It discloses the financial side effect (charging the saved card), the need for user consent, and the fallback to a secure checkout link when no card or cardholder presence is required. This goes well beyond annotations' readOnlyHint=false and idempotentHint=false.

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: purpose, call pattern, and charge behavior/fallback. No filler, immediately actionable.

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-boolean-parameter tool, the description covers the full workflow, expected outputs (price, card, limit, or checkout link), and edge cases. No output schema exists, so this description carries that burden well.

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 documents confirm's meaning (only true after explicit agreement). The description adds the orchestration detail of calling with false first to gather details, then true to execute, which enriches the parameter's usage semantics.

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

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

The description clearly states the action ('Buy more verification credits') and the context ('without leaving the conversation'). It distinguishes this from sibling tools by being the only purchasing tool among check_usage, estimate_claims, recall_claim, and verify_claims.

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 provides a concrete two-step calling pattern: first with confirm false/omitted to preview, then with confirm true after user agreement. This is explicit usage guidance, though it doesn't mention exclusions or alternative tools for other scenarios.

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?

The description adds the unique two-retriever and cross-lab audit process, plus the semantic distinction between UNSUPPORTED and false, which is not captured by the annotations. Annotations already provide readOnly/openWorld/idempotent hints, but the description enriches understanding of the tool's internal operation and verdict semantics. No contradiction found.

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, with the key information front-loaded: the core action, the verdict types, and the recommended use cases. Every sentence carries unique information—no filler or tautology.

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

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

The description explains the tool's purpose, return values (per-claim verdicts), and the meaning of each verdict, which is sufficient despite no output schema. Combined with the rich parameter descriptions and annotations, the tool is fully comprehensible for invocation. Minor gap: the credit-cost and confirmation flow are only mentioned in the confirm parameter description, not in the main description, but this is adequately covered by the schema.

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 descriptions cover all five parameters with high detail (100% coverage), including url fetching behavior, confirm's cost flow, and max_claims as a cap. The description itself adds no parameter-specific guidance, so it earns the baseline 3 for schema-heavy tools.

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

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

Description opens with 'Fact-check text against live web evidence from two independent retrievers, then have a model from a different lab audit the verdict.' This clearly names the action, resource, and distinctive process, distinguishing it from siblings like estimate_claims. The per-claim verdict list further clarifies 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 description states 'Use before relying on a factual claim, or to check your own draft answer before sending it,' providing concrete trigger conditions. It does not explicitly name alternatives or exclusions, though siblings like estimate_claims have distinct roles that are referenced in the schema's confirm parameter.

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