> ## Documentation Index > Fetch the complete documentation index at: https://docs.sequency.sh/llms.txt > Use this file to discover all available pages before exploring further. # Run AI catalyst analysis on recent news > Run an AI equity analyst agent that identifies tradeable catalysts from recent news articles, cross-referencing with the symbol's technical context (confluence scores, patterns, levels, options data). ## Rate Limit 5 requests per minute (expensive LLM call). ## Response Returns classified catalyst articles with reasoning, strategy implications, risk considerations, and overall news bias. ## OpenAPI ````yaml /api/openapi.json post /api/graph/v1/news/catalyst/{symbol} openapi: 3.1.0 info: title: Sequency Graph API description: > # Sequency Graph-Native Trading API Graph-native API for trading intelligence, built on FalkorDB. ## Features - **Screener**: Filter stocks using graph-native queries with relationship expansion - **Stock Detail**: Complete stock context with all relationships - **Confluence Scoring**: Setup quality assessment with weighted components - **Strategy Matching**: Find matching options strategies via graph traversal - **Market Context**: Current market-wide context for trading decisions ## Data Sources All data is sourced from the FalkorDB knowledge graph, populated by: - Pattern detector (Go) - Technical indicators, patterns - Graph sync service - Levels, volume profiles, news, day classification version: 1.0.0 servers: [] security: [] paths: /api/graph/v1/news/catalyst/{symbol}: post: tags: - News summary: Run AI catalyst analysis on recent news description: >- Run an AI equity analyst agent that identifies tradeable catalysts from recent news articles, cross-referencing with the symbol's technical context (confluence scores, patterns, levels, options data). ## Rate Limit 5 requests per minute (expensive LLM call). ## Response Returns classified catalyst articles with reasoning, strategy implications, risk considerations, and overall news bias. operationId: analyze_catalysts_api_graph_v1_news_catalyst__symbol__post parameters: - name: symbol in: path required: true schema: type: string title: Symbol responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/CatalystAnalysisResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' components: schemas: CatalystAnalysisResponse: properties: symbol: type: string title: Symbol description: Stock ticker symbol summary: type: string title: Summary description: 2-3 sentence executive summary catalyst_articles: items: $ref: '#/components/schemas/CatalystArticle' type: array title: Catalyst Articles description: Top articles with catalyst reasoning strategy_implications: items: $ref: '#/components/schemas/StrategyImplication' type: array title: Strategy Implications description: 1-3 strategy implications risk_considerations: items: type: string type: array title: Risk Considerations description: 2-3 risk factors overall_news_bias: type: string title: Overall News Bias description: bullish, bearish, neutral, or mixed bias_strength: type: number title: Bias Strength description: Bias strength 0-100 analyzed_at: type: string title: Analyzed At description: ISO timestamp of analysis tokens_used: anyOf: - type: integer - type: 'null' title: Tokens Used description: LLM tokens consumed type: object required: - symbol - summary - overall_news_bias - bias_strength - analyzed_at title: CatalystAnalysisResponse description: Full catalyst analysis result. HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError CatalystArticle: properties: headline: type: string title: Headline description: Article headline sentiment_score: type: number title: Sentiment Score description: Sentiment score -1 to 1 impact: type: string title: Impact description: 'Impact level: high, medium, low' catalyst_type: type: string title: Catalyst Type description: >- Catalyst classification: earnings_catalyst, momentum_catalyst, sector_rotation, event_driven, macro_shift reasoning: type: string title: Reasoning description: 1-2 sentence explanation of WHY this article is bullish/bearish type: object required: - headline - sentiment_score - impact - catalyst_type - reasoning title: CatalystArticle description: An article annotated with catalyst reasoning. StrategyImplication: properties: strategy_name: type: string title: Strategy Name description: Strategy name direction: type: string title: Direction description: bullish, bearish, or neutral timeframe: type: string title: Timeframe description: intraday, swing, or position confidence: type: number title: Confidence description: Confidence 0-100 rationale: type: string title: Rationale description: How this news catalyst connects to the strategy key_levels: items: type: string type: array title: Key Levels description: Relevant levels from graph data type: object required: - strategy_name - direction - timeframe - confidence - rationale title: StrategyImplication description: A trading strategy implied by the news catalysts. ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type input: title: Input ctx: type: object title: Context type: object required: - loc - msg - type title: ValidationError ````