World Bank & FRED Macro

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

No annotations are provided, so description must fully disclose behavior. It mentions default year but fails to specify return format, data source, or whether it is read-only. This is insufficient for a tool with no other behavioral hints.

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?

Single sentence front-loads the key purpose and default behavior. No unnecessary words; highly 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 the tool's complexity (3 parameters, no output schema, no annotations), the description is too minimal. It omits return value structure, error handling, and constraints beyond those in 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 coverage is 0% (no parameter descriptions). Description adds that 'year' defaults to most recent and 'countries' is an array, but does not explain valid indicator names, country code format, or year range. This leaves significant 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?

Description clearly states it performs side-by-side comparison of an indicator across multiple countries, with an optional year defaulting to most recent. This distinguishes it from sibling tools that search or retrieve single series (fred_search_series, wb_indicator, etc.).

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?

Description implies use when cross-country comparison is needed but provides no explicit guidance on when not to use or alternatives. It is adequate but lacks differentiation from 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, the description carries the full burden. It discloses the return fields (id, title, units, frequency), which adds value, but does not mention pagination, rate limits, or behavior on empty results. It provides moderate transparency.

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 that starts with the action ('Free-text search'), making it front-loaded and efficient. 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?

For a simple single-param search tool, the description covers the return fields, but it omits pagination, max results, and ordering. It is minimally complete but lacks information a user might expect for a search operation.

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%, and the description adds no specific details about the 'query' parameter beyond the implied 'free-text search.' The param role is obvious but lacks format, length, or example constraints.

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 performs free-text search across FRED series and lists the return fields (id, title, units, frequency). The verb 'search' and resource 'FRED series' are specific, and the tool is distinct from siblings like fred_series (specific series) and wb_search_indicator (World Bank).

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 provided on when to use this tool versus alternatives like fred_series or wb_search_indicator. The description only states what the tool does, not the context or exclusions.

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 must fully disclose behavior. It only says 'series observations' without mentioning any constraints like date range handling, pagination, error responses, or what the output looks like. This is insufficient for an agent to predict tool behavior.

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 with examples, making it very concise and front-loaded. Every word serves a purpose, though it could be slightly more structured with a clearer separation between purpose and examples.

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?

Despite low parameter count and no output schema, the description lacks essential context: it does not explain the output format (e.g., time series data), how date_from/date_to control the range, or any limitations. This makes it incomplete for effective tool use.

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 low (33%), but the description adds value by giving examples for series_id, which is the main parameter. However, date_to has no description in schema or description, and date_from's schema description is minimal. The examples partially compensate but not fully.

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 retrieves 'St Louis Fed (FRED) series observations' and provides concrete series ID examples (CPIAUCSL, UNRATE, DGS10, FEDFUNDS). This distinguishes it from sibling tools like fred_search_series (search) and World Bank 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 examples of when you would use this tool (when you have a series ID like 'CPIAUCSL') but does not explicitly state when to avoid it or when to use alternatives like fred_search_series. Usage context is implied rather than explicit.

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 must convey behavioral traits. It only states the tool returns time series data but does not mention side effects, authentication needs, rate limits, or output format. For a read-like operation, more transparency is needed.

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-loading the purpose and providing immediate value with examples and sibling tool referral. Every sentence is essential, and there is 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 four parameters (two required), no output schema, and no annotations, the description provides the core purpose and usage guidance but omits details on year range parameters, output format, error handling, and potential constraints. Adequate but not fully complete for autonomous use.

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 50% (two of four parameters described). The description adds value by listing common indicator IDs and clarifying country input format, but it does not explain the year_from and year_to parameters. This partially compensates for missing schema descriptions, but not fully.

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 retrieves a World Bank time series for a single indicator and country. It provides example indicator IDs and distinguishes itself from the sibling tool wb_search_indicator by directing users there if they don't know the ID.

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 recommends using wb_search_indicator for unknown IDs, giving clear usage context. However, it does not mention when NOT to use this tool (e.g., for multiple countries or indicators, use compare_countries instead), so the guidance is good but not exhaustive.

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 full burden. It discloses the tool returns up to 25 matching indicators and includes both IDs and names. However, it does not state what happens with no matches, query length limits, or any other behavioral traits like authentication needs.

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 extraneous information. Every word adds value and the description is front-loaded with the key 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 simple search tool with one parameter and no output schema, the description covers the essential aspects: action, resource, result limit, and return fields. It could specify that only indicator names are searched (not IDs or other metadata), but that is already implied.

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% (empty property descriptions). The description adds that the query is a 'free-text search' across indicator names, which provides minimal context beyond the schema field name. No format, examples, or constraints are given.

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 it performs a free-text search on World Bank indicator names, returning up to 25 matching IDs and names. The verb 'search' and resource 'indicator names' are specific and distinct from siblings like 'wb_indicator' which retrieves specific indicator 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 implies usage for searching indicators by name but does not provide explicit guidance on when to use this tool versus alternatives (e.g., fred_search_series for FRED data) or when not to use it. No exclusions or prerequisites are mentioned.

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