GDELT Cloud Docs — Global Event Data API & MCP

Overview

gdelt_research_system_prompt is the always-on system prompt for the research agent. It teaches:

GDELT Cloud is the differentiator. Lead with classified, quantified, linked event records, not narrative summary or web search.
Four progressive-disclosure tool categories. gdelt_cloud_*, macro_finance_*, prediction_market_*, web_research_* — always nest tool inputs inside tool_arguments when calling an executor.
Surface from question shape, not habit. A mental model maps each question shape to the correct first call.
GDELT is a graph. Events ↔ Stories ↔ Entities are linked; most non-trivial questions need 2–3 hops.
Date semantics, geography filters, semantic-search behavior, the over-filter trap, and significance scoring.
Cross-tool sequencing with GDELT first as the anchor.
Citation policy by surface, with explicit per-surface templates and a rule to quote the structured metric, not just the source.
On-demand skill loading for deeper workflow patterns: gdelt-discover-and-drill, macro-finance, prediction-markets, multi-surface-synthesis, brief-output.

gdelt_brief_system_prompt is the separate hosted Brief-agent prompt. The Brief agent preloads the shared brief-tradecraft skill plus the selected Brief-type skill (Daily Risk, SITREP, I&W Watch, Exposure Monitor) and uses a type-specific structured output schema.

What the prompt emphasizes

Area	Guidance
Anchor	Start with GDELT Cloud whenever the question touches anything it covers. Web/macro/predmarket enrich; they don’t replace.
Tool discovery	Always use `_tool_list`, inspect with `_tool_get`, execute with `*_tool_call`. Inputs go in `tool_arguments`.
Surface choice	Pick the surface from the question shape — `search_stories` for narrative, `summarize_*` for trend, `search_entities` for actor, `prediction_market.SEARCH_RELEVANT_MARKETS` for probability, etc.
Graph traversal	Walk Events ↔ Stories ↔ Entities for 2–3 hops, not single calls.
Filter discipline	The over-filter trap (subcategory + country + semantic search) is the most common failure mode. Drop the filter, not the search.
Semantic search	`search` is embedding-based on `search_events` / `search_stories` only. 3–8 focused terms. Summary tools don’t accept `search`.
Significance	Sort by `significance` for “what matters.” Quote the structured metric (significance, magnitude, propagation_potential, confidence) instead of impressionistic language.
Cross-tool sequencing	GDELT first to establish dates/actors/entities, then macro-finance / predmarket / web.
Citation	Per-surface citation templates. GDELT Cloud Story URL preferred when the GDELT artifact is the unit of evidence; source-article URL when the article itself is the more specific evidence. Never invent URLs.
Output	Adapt to task. Lookups answer directly; broad analytical briefs use BLUF / inverted-pyramid via the `brief-output` skill.
Multi-skill orchestration	Tasks spanning surfaces load all relevant skills up front. GDELT skill is the anchor.

Agent Pattern

SUMMARIZE  →  summarize_events / summarize_stories         (shape)
SEARCH     →  search_events / search_stories / search_entities  (citable candidates)
DRILL      →  get_event / get_story / get_story_articles / get_entity  (evidence)
ENRICH     →  macro_finance_* / prediction_market_* / web_research_*
SYNTHESIZE →  five divergence shapes
ANSWER     →  bottom line first, so what, watch next, evidence, details

Usage

messages = await mcp_client.get_prompt("gdelt-cloud", "gdelt_research_system_prompt")
system_text = "\n\n".join(str(msg.content) for msg in messages)

brief_messages = await mcp_client.get_prompt("gdelt-cloud", "gdelt_brief_system_prompt")
brief_system_text = "\n\n".join(str(msg.content) for msg in brief_messages)

Pair the system prompt with on-demand task skills. The research agent loads skills based on question shape — gdelt-discover-and-drill for any analytical task, plus macro-finance / prediction-markets / multi-surface-synthesis / brief-output when the task spans surfaces.

Progressive Discovery

Learn the GDELT Cloud MCP wrapper flow.

Skills

Workflow-pattern skills: discover-and-drill, macro-finance, prediction-markets, multi-surface-synthesis, brief-output.

Overview

Tools

Resources

Skills

Prompts

Integrations

gdelt_research_system_prompt

Overview

What the prompt emphasizes

Agent Pattern

Usage

Progressive Discovery

Skills

​Overview

​What the prompt emphasizes

​Agent Pattern

​Usage

​Related

Progressive Discovery

Skills

Overview

What the prompt emphasizes

Agent Pattern

Usage

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