ieUnit – neutral value reference unit

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

With no annotations provided, the description carries the full burden of disclosure. It reveals important behavioral traits: the basket is fixed, equally weighted, never rebalanced, and reference prices are immutable as of the base date. This goes beyond a bare read operation, though it does not mention potential errors or side effects, which are minimal for a simple retrieval.

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, consisting of two sentences, but it packs all essential information: the basket composition, fixed nature, reference and current prices, price movements, and the additional unit codes. There is no filler, and the structure is logical, starting with the main action.

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 parameters and no output schema, the description fully specifies what the response will contain: nine components, reference prices, current prices, price changes, and the list of unit codes for ieunit_convert. It also explains the basket's immutable design, making the tool self-contained and easily understood.

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 no parameters and the input schema is an empty object. Since there are no parameters, the description need not add any parameter semantics, and the baseline for a zero-parameter tool is 4. The description adds no irrelevant parameter information.

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: 'Get the composition of the ieUnit basket,' and immediately enumerates the exact contents (nine fixed components, reference prices, current prices, price movements). It clearly distinguishes this from sibling tools like ieunit_convert or ieunit_compare by focusing on basket composition rather than conversion or comparison.

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 basket composition or reference prices are needed—but it does not explicitly say when to use it versus alternatives or provide any exclusions. The note about returning unit codes accepted by ieunit_convert gives a practical linkage but falls short of explicit guidance.

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

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

With no annotations, the description carries the full transparency burden. It usefully explains that results are measured in ieUnit and that a negative figure means loss of value relative to the ieUnit, but it does not disclose the exact return format (single value vs. series), pagination, or edge cases.

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 concise sentences that front-load the action, provide concrete examples, and add interpretive guidance. Every sentence contributes meaningful information without 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?

The description covers purpose, unit, period, available components, and result interpretation, while the schema fully documents the optional dates. However, because there is no output schema, the description stops short of specifying the exact response structure, which is the main 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?

The input schema already covers all three parameters with descriptions, including date defaults and the component enum. The tool description repeats the component list but does not add parameter-specific meaning, so the baseline 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 and resource: 'Compare one basket component against the ieUnit over a period of time', and clarifies the unit of measurement. It also distinguishes itself from siblings by emphasizing period-based comparison and neutral reference, which sets it apart from convert, value, and history 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 description gives clear use cases ('Answers questions such as how the Swiss franc, gold or Bitcoin held their value against a neutral reference'), which implies when to use the tool. However, it does not explicitly state alternatives or when not to use it, so it falls short of a 5.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It mentions that the tool 'Works in both directions' and instructs to use 'ieUnit' as the unit code. However, it does not disclose potential side effects (e.g., whether it modifies any data), error conditions, or return format. For a conversion tool, the read-only nature is implied but not explicitly stated, leaving some ambiguity.

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, front-loaded with the primary purpose. It delivers essential information without unnecessary detail. Every sentence contributes: purpose/scope, directionality and example, and a pointer to sibling tool. This is a model of concise, structured tool documentation.

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 three required parameters, no output schema, and no annotations, the description covers the essential operational aspects: unit types, direction, and how to obtain codes. It lacks some details like error behavior or exact return structure, but given the simplicity and the existing schema, it is sufficiently complete for an agent to invoke the tool 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 each parameter described. The description adds value beyond the schema by providing concrete examples ('250 CHF to ieUnit') and clarifying the 'ieUnit' code usage. This reinforces the schema and helps the agent understand valid inputs, going beyond the basic parameter descriptions.

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 function: 'Convert an amount between the ieUnit and about 60 other units'. It specifies the types of units (fiat, crypto, gold, silver, XIN) and provides concrete examples. It also distinguishes from sibling tools by mentioning ieunit_basket for retrieving unit codes.

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 this tool: for conversions between ieUnit and other units. It explicitly references an alternative, telling the user to 'Call ieunit_basket first if you need the list of available unit codes.' This guidance helps an agent choose the right tool but does not explicitly state when not to use this tool relative to other siblings like compare or history.

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

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

With no annotations, the description carries the full burden for behavioral disclosure. It reveals return shape (dated series plus summary figures), the fixed base date, starting value, and the heavy result warning for daily resolution. However, it omits details like auto-thinning (mentioned in schema) and any potential error behavior, so it is good but not exhaustive.

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: purpose, output summary, and resolution guidance. It is front-loaded with the core action and key historical anchor, with no fluff or redundant phrasing.

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 has no output schema and no annotations, the description adequately conveys what results to expect (dated series + summary figures) and provides the necessary context for typical usage. It is not overly complex, but it lacks edge-case details (e.g., invalid date ranges, exact handling of thinning) which prevents a 5.

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 all parameters already described in the input schema. The description mainly repeats the default date and resolution behavior (start date 2017-01-10, monthly default) without adding new parameter-specific nuance. Baseline 3 is appropriate since the schema does the heavy lifting.

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+resource+scope: "Get the historical value of the ieUnit in USD since its fixed base date 2017-01-10." It clearly distinguishes from siblings by saying "Use this for questions about how the ieUnit developed over time," which differentiates it from value/convert/compare 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 description gives explicit usage context ("Use this for questions about how the ieUnit developed over time") and explains resolution trade-offs ("Defaults to monthly resolution; daily data is available but produces large results over long ranges"). It does not explicitly name alternative tools or state when not to use it, so it falls short of a 5.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool returns a 'plain-text explanation' and outlines the exact topics covered, which effectively communicates read-only behavior and output content. It does not mention potential limitations like language or formatting, but for this simple methodology tool, the disclosure is strong.

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 yet information-dense, using a single sentence to enumerate the key content and a second sentence to provide usage context. Every clause earns its place, and the main 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?

Given the tool's simplicity (no parameters, no output schema), the description fully covers what the tool does, what it returns, and when to use it. The list of returned content is sufficiently detailed, making the tool self-explanatory even without additional structured information.

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 baseline is 4. The description needs to add no parameter meaning, and indeed none is needed. The schema is empty with 100% coverage, so there is nothing further to clarify.

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 providing an authoritative plain-text explanation of the ieUnit's definition and calculation, listing specific content areas (geometric mean formula, fixed base date, data sources, governance rules, and what it is NOT). This distinguishes it from sibling tools like ieunit_convert or ieunit_history, which focus on calculations or historical data.

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 explicit usage guidance: 'Call this before describing or characterising the ieUnit to a user.' This makes the intended context clear. However, it does not explicitly mention when not to use it or name alternative tools for other tasks, so it stops short of full when/when-not 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?

No annotations were provided, so the description carries the behavioral burden. It discloses that values are recalculated once per day, returns multiple data points (USD, CHF, EUR, 24h change, last update date), and explains the underlying basket, giving the agent a clear understanding of the tool's behavior and output.

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 long, front-loads the main purpose, and provides essential context without unnecessary fluff. The explanation of what an ieUnit is adds value but is not overly verbose.

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?

Without an output schema, the description adequately explains what the tool returns (value in USD, CHF, EUR, 24-hour change, last update date) and the freshness policy. It is complete enough for a simple single-parameter 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%, and the schema's parameter description already explains the 'currency' enum and that all three currencies are always included. The description adds no additional parameter semantics beyond what the schema provides, so 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 states the tool's function with a specific verb and resource: 'Get the current value of one ieUnit.' It also distinguishes the tool from siblings by focusing on the 'current' value and mentioning daily recalculation, differentiating it from ieunit_history or ieunit_compare.

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 a direct usage example: 'Use this for questions like "what is one ieUnit worth right now"' which clearly indicates when to use the tool. It does not explicitly state when not to use it, but for a simple current-value tool this is sufficient guidance.

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