reference-data

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

No annotations are provided, so the description carries full responsibility. It fully discloses key behaviors: returns verdict, margin, floor, and legal instrument; never guesses cross-period conversions; and honestly indicates when no enforceable floor exists. The payment mechanism and api_key usage are also explained.

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 (three sentences) and front-loaded with the core purpose. Each sentence adds value: primary function, outputs and caveats, payment details. No wasted words 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?

Given no output schema, the description adequately covers expected return values (verdict, margin, statutory floor, legal instrument) and edge cases (missing floor, period mismatch). All parameters are described both in schema and enriched by the description. The tool's behavior is fully specified for an AI agent to use 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?

Schema coverage is 100% with parameter descriptions, but the description adds meaningful context: amount is in country's currency, period must exactly match the statutory floor's period, and country uses ISO codes. The description reinforces the period constraint, which is present in the schema but clarified further.

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's purpose: checking if a salary is at, above, or below the statutory minimum wage for a given country. It specifies the outputs (verdict, margin, statutory floor, legal instrument) and distinct behaviors (honest statuses for missing floors or period mismatches). The tool is differentiated from sibling tools, which cover taxes, holidays, and time series.

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 provides clear context on when to use the tool (minimum wage compliance check) and mentions optional payment mechanisms (api_key or x402). It does not explicitly state when not to use it or compare to siblings, but the sibling list shows no overlap, so the context is sufficient.

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 fully discloses behavioral traits: cost ($0.05), use of marginal brackets, handling of inflation-indexed units, return of per-bracket details and rates, and that it does not apply reliefs/social security. It also explains authentication via api_key or x402 payment.

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 informative and front-loaded with cost and main purpose. Some redundancy (e.g., tax unit handling) could be trimmed, but overall concise and well-structured.

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 input semantics, behavior, and return value expectations (per-bracket workings, effective rate). Without an output schema, it provides sufficient context for an agent to understand what the tool returns and how payment works.

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% with param descriptions, but the description adds extra context (e.g., handled countries, period basis). However, there is an inconsistency: the described countries (Colombia, Chile, etc.) are not in the enum, potentially confusing agents. Baseline 3 with added value offset by discrepancy.

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 computes statutory income tax on taxable income for a given country, with specific verb and resource. It distinguishes itself from siblings like compute_vat and check_minimum_wage by focusing on income tax and marginal brackets.

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 provides clear context on when to use (computing income tax on taxable income) and what not to do (not net pay, caller handles reliefs). It mentions payment options but does not explicitly exclude alternatives or compare with 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 fully discloses behavioral traits: it is a paid tool ($0.02), uses current statutory rates, handles composite rates, explains mode behavior, and clarifies that without an api_key the response explains payment via x402.

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 three sentences long, front-loaded with cost and purpose. Every sentence adds essential information without redundancy, fitting within typical length constraints.

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

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

Given the tool's complexity (4 params, modes, composite rates) and no output schema, the description covers most aspects but lacks details on the exact output structure beyond 'net, tax and gross' and does not mention error handling or rate validity.

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 has 100% coverage, so the description adds meaning beyond it: it explains mode options (add/extract), how country rates are applied (including composite levies like Ghana VAT+NHIL+GETFund), and the api_key's role in payment. However, the description mentions Ghana as an example while the schema only lists EU countries, which may mislead.

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 computes VAT breakdown (net, tax, gross) using current statutory rates, including composite rates. It names the resource (amount and country) and actions (add or extract), distinguishing it from sibling tools like compute_income_tax or get_public_holidays.

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 implicitly guides when to use each mode (add vs extract) and mentions the api_key option, but does not explicitly state when to prefer this tool over siblings, nor does it provide exclusion criteria.

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 provided, so description bears full burden. It discloses key behaviors: weekends handling (including Egypt's Fri-Sat), statutory holidays applied, output includes holiday names and next working day, range limit. Lacks details on errors or rate limits, but sufficient for typical use.

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 no wasted words. First sentence packs the core functionality, second sentence handles payment and API key usage. Perfectly front-loaded and efficient.

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 explains what the output includes (holiday names, next working day). It covers pricing, limit, and authentication method. With 4 parameters (3 required), this is complete for an agent to invoke 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?

Schema coverage is 100% (baseline 3). Description adds value beyond schema by noting the range max of 366 days (not in schema) and clarifying that from/to are inclusive. The country parameter's enum values are listed in schema, but description reinforces their meaning.

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 counts working days in a date range for a specific country, applying weekends and statutory holidays. It distinguishes from siblings like get_public_holidays by focusing on counting and including holiday names and next working day.

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?

Provides clear usage context: range max 366 days, pricing ($0.02), and how to pay if no api_key. It does not explicitly state when not to use or compare with alternatives, but the purpose is specific enough to guide selection.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is free and cites official government sources, but does not address rate limits, response format, or error behavior (e.g., invalid country). The enum in the schema mitigates some parameter issues.

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, well-structured sentence that is front-loaded with key information ('FREE', 'Official public-holiday calendar'), 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 the tool's simplicity (one parameter, no nested objects, no output schema), the description covers the essential aspects: free, official, includes movable holidays, cites source. It is nearly complete; an example of returned data would be a minor improvement.

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% with a single parameter, and the description does not add meaning beyond what the schema provides. The description's mention of 'official' and 'gazetted' does not directly enhance parameter understanding.

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 function: retrieving public holidays for supported countries, including movable holidays, and distinguishes it from sibling tools like check_minimum_wage or compute_income_tax, which serve different purposes.

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 it is 'FREE', implying no cost, but does not explicitly state when to use this tool versus alternatives or provide exclusion criteria. It assumes the user understands that public holidays are distinct from other 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 provided, so description carries the burden. It discloses cost ($0.005), payment mechanism (x402), and response contents (source citation, effective date, last-confirmed date, staleness flag). Does not mention rate limits but covers key behavioral aspects.

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, front-loaded with purpose and cost. Second sentence covers payment/API key. Efficient and no wasted words, though could be more structured with bullet points.

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 3 parameters and no output schema, description provides adequate context: what it does, cost, payment, response fields. Lacks explicit output format but is sufficient for basic usage.

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. Description gives examples for the series parameter but adds little new meaning beyond schema. No additional info for country (already enum) or api_key.

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 clearly states the tool retrieves the 'Current value of a reference series' and gives examples like policy-rate, vat, minimum-wage. It distinguishes from siblings like get_series_history (historical data) and list_series (listing available series).

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?

Provides payment/authentication guidance ('Pass api_key... otherwise response explains how to pay via x402'). Implicitly indicates use for current values vs. history, but does not explicitly state when not to use or name 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?

No annotations provided; description discloses pricing and date filtering behavior. Does not state read-only nature or error handling, but adds meaningful context.

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 covering purpose, filtering, and payment. 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?

Covers most needed context: purpose, parameters, payment. Lacks description of return format or error cases, but schema is thorough.

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 description adds little beyond schema. Mentions date format and api_key usage, but these are already in 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?

Clearly states the tool retrieves historical values of a reference series with optional date filtering. Distinguishes from siblings like get_series (current values) and get_snapshot.

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?

Provides pricing information and guidance on using api_key or payment via x402. Lacks explicit when-to-use vs alternatives, but context is clear.

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 call costs $0.02 and explains the payment mechanism via x402 if no api_key is provided. This adds behavioral context beyond the input schema. No annotations exist to contradict.

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 efficient sentences with front-loaded cost and purpose. Every word earns its place 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?

Given the tool's simplicity (one optional param, no output schema), the description covers purpose, cost, and payment flow adequately. It lacks details about response structure, but the purpose implies a comprehensive data dump.

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 (api_key) is described as optional and tied to payment, adding meaningful context beyond the schema's simple 'API key' description. Schema coverage is 100%, but the description enhances understanding.

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 returns a snapshot of every series for every country in one call, with a specific verb and resource, distinguishing it from siblings like get_series (single series) or list_series.

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 advises the agent to pass an api_key if available and explains the payment flow otherwise, providing clear guidance on usage. However, it does not explicitly compare to alternative tools or specify when not to use 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?

No annotations are provided, so the description carries full burden. It states 'FREE' and describes the return content, but does not explicitly address safety (e.g., non-destructive), rate limits, or authentication. The straightforward read-only nature mitigates but doesn't fully compensate.

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: first enumerates output contents, second gives usage direction. Every word is meaningful 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?

With no parameters or output schema, the description adequately explains the tool's purpose and output. It lacks details on result size or pagination, but for a listing tool this is sufficient.

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 the schema is empty (coverage 100% trivial). The description adds value by explaining what the output contains, which is necessary given no output 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 lists a catalog of euroref reference-data series, detailing contents (countries, series IDs, descriptions, freshness, URLs). It distinguishes from sibling tools like get_series which require specific series IDs.

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 'Call this first to discover what data exists,' indicating primary usage before other sibling tools. It doesn't mention when not to use it or name alternatives, but the context is clear.

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