deep_research
ChatGPTPerform in-depth research on a topic by combining verified claims from Factagora's database, live news, and time-series analysis into a structured report. Returns a summary, thematic sections, timeline data, and cited sources. Use this when the user wants a comprehensive research report on a topic rather than a simple search result.
deep_research
ChatGPTPerform in-depth research on a topic by combining verified claims from Factagora's database, live news, and time-series analysis into a structured report. Returns a summary, thematic sections, timeline data, and cited sources. Use this when the user wants a comprehensive research report on a topic rather than a simple search result.
fact_check
ChatGPTVerify whether a claim is TRUE, FALSE, or UNCERTAIN using Factagora's internal database. Returns a verdict with confidence score, summary explanation, and cited sources. Use this when the user asks "is this true?", wants a quick fact-check on a specific statement, or needs a confidence-rated verdict with sourced reasoning.
fact_check
ChatGPTVerify whether a claim is TRUE, FALSE, or UNCERTAIN using Factagora's internal database. Returns a verdict with confidence score, summary explanation, and cited sources. Use this when the user asks "is this true?", wants a quick fact-check on a specific statement, or needs a confidence-rated verdict with sourced reasoning.
find_evidence
ChatGPTFind credibility-scored evidence for a claim from Factagora's internal database and live news sources. Returns evidence items with source URLs, type (DATA/EXPERT/NEWS/FACT_CHECK), and credibility scores. Use this when the user wants to verify a statement, find supporting or contradicting sources, or needs a list of references for a specific claim.
find_evidence
ChatGPTFind credibility-scored evidence for a claim from Factagora's internal database and live news sources. Returns evidence items with source URLs, type (DATA/EXPERT/NEWS/FACT_CHECK), and credibility scores. Use this when the user wants to verify a statement, find supporting or contradicting sources, or needs a list of references for a specific claim.
get_argument_map
ChatGPTGet the argument map graph for a specific claim or prediction. Shows how sub-claims relate to the root claim through SUPPORTS, CONTRADICTS, QUALIFIES, DEPENDS_ON, and other relationships. Returns a hierarchical graph showing the evidence structure, agent-derived arguments, and challenge history. Use this when you need to understand the detailed argumentation structure behind a claim.
get_argument_map
ChatGPTGet the argument map graph for a specific claim or prediction. Shows how sub-claims relate to the root claim through SUPPORTS, CONTRADICTS, QUALIFIES, DEPENDS_ON, and other relationships. Returns a hierarchical graph showing the evidence structure, agent-derived arguments, and challenge history. Use this when you need to understand the detailed argumentation structure behind a claim.
get_factblock
ChatGPTRetrieve detailed information for a specific claim or prediction by ID. Use this only when the user provides a direct claim URL/ID, or when you need to verify specific details not available in search results. For most queries, search_claims/search_predictions already provide comprehensive information including evidence, debate, and graph visualization.
get_factblock
ChatGPTRetrieve detailed information for a specific claim or prediction by ID. Use this only when the user provides a direct claim URL/ID, or when you need to verify specific details not available in search results. For most queries, search_claims/search_predictions already provide comprehensive information including evidence, debate, and graph visualization.
search_claims
ChatGPTQuery Factagora's evidence knowledge graph for claims analyzed through adversarial multi-agent verification. Returns structured data that goes beyond web search or training data: verdicts (TRUE/FALSE/UNVERIFIED), credibility-scored evidence with sources, temporal context showing how claims evolved over time, and full adversarial debate where AI agents with opposing perspectives (skeptic, analyst, optimist) argue positions with confidence scores and cited reasoning. Use this when the user questions the truth of a statement, asks "is it true that...", needs evidence-backed analysis on a controversial topic, or wants to understand how a claim has held up over time. Queries must be in English.
search_claims
ChatGPTQuery Factagora's evidence knowledge graph for claims analyzed through adversarial multi-agent verification. Returns structured data that goes beyond web search or training data: verdicts (TRUE/FALSE/UNVERIFIED), credibility-scored evidence with sources, temporal context showing how claims evolved over time, and full adversarial debate where AI agents with opposing perspectives (skeptic, analyst, optimist) argue positions with confidence scores and cited reasoning. Use this when the user questions the truth of a statement, asks "is it true that...", needs evidence-backed analysis on a controversial topic, or wants to understand how a claim has held up over time. Queries must be in English.
search_news
ChatGPTSearch recent news articles from global news sources (GDELT). Returns article titles, URLs, publication dates, and source domains. Use this when the user asks about recent news, current events, or wants news coverage of a topic. For fact-checked analysis with AI agent verdicts, use search_claims or search_predictions instead.
search_news
ChatGPTSearch recent news articles from global news sources (GDELT). Returns article titles, URLs, publication dates, and source domains. Use this when the user asks about recent news, current events, or wants news coverage of a topic. For fact-checked analysis with AI agent verdicts, use search_claims or search_predictions instead.
search_predictions
ChatGPTQuery Factagora's evidence knowledge graph for predictions and forecasts with adversarial multi-agent analysis. Returns structured data unavailable through web search: consensus positions (YES/NO/UNCERTAIN) with confidence scores, credibility-scored supporting evidence, causal reasoning chains, and adversarial debate where AI agents with competing viewpoints assess likelihood with cited arguments. Use this when the user asks "will X happen?", wants to assess the likelihood of a future outcome, needs structured forecast analysis, or wants to understand the causal factors behind a prediction. Queries must be in English.
search_predictions
ChatGPTQuery Factagora's evidence knowledge graph for predictions and forecasts with adversarial multi-agent analysis. Returns structured data unavailable through web search: consensus positions (YES/NO/UNCERTAIN) with confidence scores, credibility-scored supporting evidence, causal reasoning chains, and adversarial debate where AI agents with competing viewpoints assess likelihood with cited arguments. Use this when the user asks "will X happen?", wants to assess the likelihood of a future outcome, needs structured forecast analysis, or wants to understand the causal factors behind a prediction. Queries must be in English.
