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Oecd List Agencies

oecd_list_agencies
Read-onlyIdempotent

List OECD SDMX agencies, the directorate each belongs to, and the number of dataflows each publishes. Use to discover agency IDs before filtering oecd_search_datasets by department.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
sourceNoData source attribution — always "OECD".
agenciesNoAgencies and their dataflow counts, sorted descending by count.
total_agenciesNoTotal number of distinct agencies.
total_dataflowsNoTotal number of dataflows across all agencies.

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds value by naming the returned content (agencies, directorate, dataflow counts) and its intended role in a search workflow. It does not go further into behavior such as pagination, ordering, or how open-world results should be interpreted, but for a zero-parameter list tool this is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The first sentence states what the tool returns, and the second gives the concrete workflow purpose. Every word earns its place and the key action is front-loaded.

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

Completeness5/5

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

For a zero-parameter, read-only, idempotent listing tool with an output schema present, the description covers the essential information: what is returned and why an agent would invoke it. The annotations handle side-effect concerns, and the output schema handles return structure details.

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

Parameters4/5

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

The tool has zero parameters, so the input schema is complete by definition and there is nothing for the description to clarify. Baseline for no-parameter tools is 4, and the description appropriately avoids inventing parameter information that does not exist.

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

Purpose5/5

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 ('List OECD SDMX agencies') and specifies the exact output fields ('directorate each belongs to, and the number of dataflows each publishes'). It differentiates itself from siblings by positioning itself as the precursor to filtering oecd_search_datasets, so an agent can distinguish it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit use case: discover agency IDs before filtering oecd_search_datasets by department. It names the sibling tool and the workflow context. It does not explicitly state when not to use it, but the positive guidance is specific enough to route an agent effectively.

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

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TDQS

A4.5/5.0
Disambiguation5/5

Each tool occupies a distinct stage of the OECD data workflow: search/agency discovery, dataset structure, dimension values, observation querying, and SQL analysis of spilled results. The two query tools are differentiated by source (SDMX vs staged DataCanvas tables), and the two metadata tools are differentiated by purpose (key structure vs codelist values).

Naming Consistency4/5

Most tools follow an oecd_<verb>_<noun> pattern (get, list, query, search), and all share the oecd_ prefix and snake_case. The two dataframe tools shift to oecd_dataframe_<verb>, a minor but noticeable ordering deviation.

Tool Count5/5

Seven tools is well-scoped for an OECD data access server: discovery, metadata, dimension values, observation query, and large-result SQL handling. There is no apparent bloat or overly thin coverage.

Completeness5/5

The set covers the full journey from finding datasets and agencies, learning the SDMX key structure, resolving dimension codes, fetching observations, and analyzing spilled datasets with SQL. This is a complete read-only workflow for the domain.