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request_chart

AUTARIO-INTERNAL high-level chart request (admin only): the server builds the Plotly chart from a catalog dataset (World Bank, FRED, Eurostat, OECD, WHO, IMF, SEC), you do NOT build a spec, but you DO write the insight. TWO-STEP FLOW for a first-try hit: (1) PREPARE - call with dataset_id/query and NO insight; the server composes the chart deterministically and returns charted_entities (the exact entity set it drew, each with latest/peak/trough/average) + chart_type, WITHOUT publishing. IMPORTANT: a multi-country dataset is charted as an ENTITY FAMILY (the top economies, G7, the aggregate rows...), so your insight is verified ONLY against the entities actually in charted_entities | anchor every claim on one of THOSE entities and cite only THOSE per-entity values. (2) PUBLISH - call again with the same dataset_id/query PLUS your 2-3 sentence insight; the server verifies it against the real data (number-hallucination gate) and publishes, returning the URL. The server runs NO LLM of its own (you write the insight). One request = one chart. On reject it returns 422 naming WHICH number/claim failed + the charted_entities + available anchors so you fix in one step. Use THIS over create_chart_from_spec whenever you want "a good chart for this dataset/topic" without assembling a full Builder spec. Non-admin keys receive 403; third parties use create_chart_from_spec / publish_chart.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeNoOPTIONAL time-range hint (e.g. "2010-2024"). Soft preference; the server uses the actual data span.
queryNoFree-form topic/search string the server resolves to the best chartable dataset (e.g. "global inflation", "US unemployment rate"). Use instead of dataset_id when you only know the topic. dataset_id wins if both are given.
regionNoOPTIONAL hint to focus a multi-country dataset on a region/entity (e.g. "G7", "Europe"). Soft preference; the server picks the final entity set.
insightNoYour 2-3 sentence data insight. OMIT IT on the PREPARE call to receive charted_entities + anchors first; SEND IT on the PUBLISH call to verify + publish. Every cited number MUST be one of the per-entity values in charted_entities (latest/peak/trough/average) returned by the prepare call. The server verifies it against the real data and publishes on pass, or returns the failing number(s) + charted_entities + anchors on fail. The server does NOT write this for you.
chart_typeNoOPTIONAL hint (line | bar | snapshot). The server still owns the final chart-type decision based on the data shape; this is a soft preference only.
dataset_idNoUUID of the dataset to chart (from search_datasets / discover_by_topic / list_chart_candidates). Preferred when you already know the dataset.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

With annotations giving only generic hints and no readOnly/destructive guidance, the description carries the behavioral burden and delivers richly. It discloses the two-step prepare/publish flow, that the prepare call does NOT publish, that the publish call verifies numbers, that the server runs no LLM, and that rejects return 422 with failing claims and anchors.

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

Conciseness4/5

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

The description is long and uses heavy capitalization, but the tool has a genuinely complex two-step flow, six optional parameters, auth constraints, and verification behavior. Nearly every sentence earns its place; it could be lightly restructured for readability without losing information.

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?

Given the tool's complexity and lack of an output schema, the description is complete enough for an agent to invoke it correctly. It covers auth, the prepare/publish protocol, what the server returns, the number-hallucination gate, error response contents, and the relationship to sibling tools.

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

Parameters5/5

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

Although schema coverage is 100%, the description adds crucial parameter semantics beyond the schema. It explains that insight must be omitted on the prepare call and sent on the publish call, that every cited number must come from charted_entities, and that time/region/chart_type are soft preferences while dataset_id wins over query.

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 states a specific verb and resource: it requests a high-level chart that the server builds from a catalog dataset, with the user writing only the insight. It clearly distinguishes this from create_chart_from_spec by saying you do NOT build a Builder spec, so an agent can tell siblings apart.

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

Usage Guidelines5/5

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

It explicitly tells the agent when to use this tool over create_chart_from_spec: whenever a good chart is wanted without assembling a full Builder spec. It also gives exclusions and alternatives: non-admin keys receive 403 and third parties should use create_chart_from_spec / publish_chart.

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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