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gdelt_timeline

Track GDELT query coverage volume, tone, or language/country distribution over time; filter by date range, domain, country, or language.

Instructions

Coverage volume or tone over time for a GDELT query. Returns how coverage of the required GDELT query changes over time, as dated points. metric picks volume (the default, share of monitored articles), volume_raw (matching article count), tone (average sentiment), or lang and country for one series per language or country. Filter with country, language, domain, timespan or from and to; smooth runs 0 to 30 (default 0).

Input Schema

NameRequiredDescriptionDefault
toNoEnd of an absolute time window. Same formats as from.
fromNoStart of an absolute time window. Accepts YYYY-MM-DD, RFC3339, or GDELT's raw YYYYMMDDHHMMSS. Cannot be combined with timespan.
queryYesGDELT query string. Same syntax as gdelt-search's query.
domainNoConvenience domain filter, appended to the query as domain:VALUE.
metricNoTimeline metric. lang and country return one series per language/country instead of one aggregate series.
smoothNoMoving-window smoothing applied to the timeline, in steps. 0 disables smoothing.
countryNoConvenience source-country filter, appended to the query as sourcecountry:VALUE.
languageNoConvenience source-language filter, appended to the query as sourcelang:VALUE.
timespanNoRelative time window ending now, e.g. 1h, 2d, 1w, 3m. Cannot be combined with from/to.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.17.5
    • addedInput schema / properties / metric / enum
      Added value: +[
+  "volume",
+  "volume_raw",
+  "tone",
+  "lang",
+  "country"
+]
  2. Addedv1.16.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries more burden. It does disclose output shape ('as dated points', one series per language/country) and metric defaults, which is genuine behavioral context, but it omits return-format details, aggregation granularity, and any access/rate constraints.

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?

Front-loaded with the core purpose, then a compact enumeration of metric options and filters. Dense but nearly every clause earns its place; slightly list-heavy but not padded.

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

Completeness4/5

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

For a 9-parameter, no-output-schema, no-annotation read tool, the description covers what the return looks like conceptually and the key metric variants. It could say more about series granularity and time bucketing, but nothing essential to a correct call is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents every parameter including enum values and from/to vs timespan exclusivity. The description adds only marginal value: the default metric (volume) and the 0-30 range for smooth, which the schema does not state.

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

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: coverage volume or tone over time for a GDELT query, returning dated points. It is clearly a time-series tool, but it never names or contrasts with close siblings like gdelt_tonechart or gdelt_search, leaving sibling differentiation to inference.

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

Usage Guidelines3/5

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

Usage is implied by the wording (use it to see how coverage/metrics change over time) but there is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named despite several adjacent GDELT tools existing.

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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