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Documentation Index

Fetch the complete documentation index at: https://docs.gdeltcloud.com/llms.txt

Use this file to discover all available pages before exploring further.

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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.

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What the prompt emphasizes

AreaGuidance
AnchorStart with GDELT Cloud whenever the question touches anything it covers. Web/macro/predmarket enrich; they don’t replace.
Tool discoveryAlways use *_tool_list, inspect with *_tool_get, execute with *_tool_call. Inputs go in tool_arguments.
Surface choicePick 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 traversalWalk Events ↔ Stories ↔ Entities for 2–3 hops, not single calls.
Filter disciplineThe over-filter trap (subcategory + country + semantic search) is the most common failure mode. Drop the filter, not the search.
Semantic searchsearch is embedding-based on search_events / search_stories only. 3–8 focused terms. Summary tools don’t accept search.
SignificanceSort by significance for “what matters.” Quote the structured metric (significance, magnitude, propagation_potential, confidence) instead of impressionistic language.
Cross-tool sequencingGDELT first to establish dates/actors/entities, then macro-finance / predmarket / web.
CitationPer-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.
OutputAdapt to task. Lookups answer directly; broad analytical briefs use BLUF / inverted-pyramid via the brief-output skill.
Multi-skill orchestrationTasks spanning surfaces load all relevant skills up front. GDELT skill is the anchor.

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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

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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.

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Related

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.