{ "name": "My workflow 7", "nodes": [ { "parameters": { "httpMethod": "POST", "path": "earnings-call", "responseMode": "responseNode", "options": {} }, "id": "962bd8d3-78be-4a04-81f1-313a0f886826", "name": "Webhook: Receive Transcript", "type": "n8n-nodes-base.webhook", "typeVersion": 2, "position": [ -1760, 144 ] }, { "parameters": { "jsCode": "const body = $input.first().json.body;\n\nconst errors = [];\n\nif (!body.transcript_text || body.transcript_text.trim().length < 100) {\n errors.push('transcript_text is required and must be at least 100 characters');\n}\nif (!body.company_name) {\n errors.push('company_name is required');\n}\nif (!body.call_date) {\n errors.push('call_date is required (YYYY-MM-DD)');\n}\n\nif (errors.length > 0) {\n return [{ json: { valid: false, errors, status: 400 } }];\n}\n\n// Build slugs\nconst ticker = (body.ticker || body.company_name.replace(/\\s+/g,'').substring(0,6)).toUpperCase();\nconst fiscal_quarter = body.fiscal_quarter || 'UNKNOWN';\nconst quarter_slug = fiscal_quarter.replace(/\\s+/g,'-').toUpperCase();\n\nreturn [{\n json: {\n valid: true,\n company_name: body.company_name,\n ticker,\n call_date: body.call_date,\n fiscal_quarter,\n fiscal_year: body.fiscal_year || null,\n call_type: body.call_type || 'quarterly',\n transcript_source: body.transcript_source || 'manual',\n transcript_text: body.transcript_text,\n word_count: body.transcript_text.trim().split(/\\s+/).length,\n quarter_slug\n }\n}];" }, "id": "a0bdafbf-44be-44ba-891e-ccbaeed22105", "name": "Validate Input", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -1536, 144 ] }, { "parameters": { "operation": "executeQuery", "query": "INSERT INTO earnings_calls (company_name, ticker, call_date, fiscal_quarter, fiscal_year, call_type, raw_transcript, transcript_source, word_count, processing_status)\nVALUES (\n '{{ $json.company_name }}',\n '{{ $json.ticker }}',\n '{{ $json.call_date }}'::DATE,\n '{{ $json.fiscal_quarter }}',\n {{ $json.fiscal_year || 'NULL' }},\n '{{ $json.call_type }}',\n '{{ $json.transcript_text }}',\n '{{ $json.transcript_source }}',\n {{ $json.word_count }},\n 'processing'\n)\nRETURNING id, company_name, ticker, fiscal_quarter;", "options": {} }, "id": "2b264b5a-d777-459e-8943-42d20a835015", "name": "DB: Insert earnings_call", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ -1328, 128 ] }, { "parameters": { "assignments": { "assignments": [ { "id": "a1", "name": "earnings_call_id", "value": "={{ $json.id }}", "type": "string" }, { "id": "a2", "name": "company_name", "value": "={{ $json.company_name }}", "type": "string" }, { "id": "a3", "name": "ticker", "value": "={{ $json.ticker }}", "type": "string" }, { "id": "a4", "name": "fiscal_quarter", "value": "={{ $json.fiscal_quarter }}", "type": "string" }, { "id": "a5", "name": "transcript_text", "value": "={{ $('Validate Input').first().json.transcript_text }}", "type": "string" }, { "id": "a6", "name": "quarter_slug", "value": "={{ $('Validate Input').first().json.quarter_slug }}", "type": "string" } ] }, "options": {} }, "id": "8a6a1b93-7f36-4119-b87f-c4e6d6f47cf1", "name": "Set Call Context", "type": "n8n-nodes-base.set", "typeVersion": 3.4, "position": [ -1104, 128 ] }, { "parameters": { "jsCode": "const response = $input.first().json;\nconst callContext = $('Set Call Context').first().json;\n\n// Groq format\nconst rawText = response.choices?.[0]?.message?.content || '{}';\nlet parsed;\ntry {\n const clean = rawText.replace(/```json|```/g, '').trim();\n parsed = JSON.parse(clean);\n} catch(e) {\n return [{ json: { error: 'Section parse failed: ' + e.message, raw: rawText, earnings_call_id: callContext.earnings_call_id } }];\n}\n\n// Enrich each section with call context\nconst sections = (parsed.sections || []).map((s, idx) => ({\n ...s,\n earnings_call_id: callContext.earnings_call_id,\n company_name: callContext.company_name,\n ticker: callContext.ticker,\n fiscal_quarter: callContext.fiscal_quarter,\n quarter_slug: callContext.quarter_slug,\n transcript_text: callContext.transcript_text,\n section_order: s.section_order || idx + 1\n}));\n\nreturn sections.map(s => ({ json: s }));" }, "id": "f70f9ffd-a452-4def-ae96-4fba36e5a357", "name": "Process Section Response", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ -656, 128 ] }, { "parameters": { "operation": "executeQuery", "query": "INSERT INTO transcript_sections (earnings_call_id, section_type, speaker_name, speaker_role, speaker_firm, section_text, section_order)\nVALUES (\n '{{ $json.earnings_call_id }}'::UUID,\n '{{ $json.label || $json.section_type }}',\n {{ $json.speaker_name ? \"'\" + $json.speaker_name + \"'\" : 'NULL' }},\n '{{ $json.speaker_role || \"Other\" }}',\n {{ $json.speaker_firm ? \"'\" + $json.speaker_firm + \"'\" : 'NULL' }},\n '{{ $json.content || $json.section_text }}',\n {{ $json.section_order }}\n)\nRETURNING id, section_type, speaker_role;", "options": {} }, "id": "f5a7b728-ff9f-4ea1-aee4-3b11be2c3bb0", "name": "DB: Insert transcript_section", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ -448, 128 ] }, { "parameters": { "mode": "expression", "output": "={{ $('Process Section Response').item.json.section_type?.toLowerCase().includes('question') || $('Process Section Response').item.json.label?.toLowerCase().includes('question') ? 1 : ($('Process Section Response').item.json.section_type?.toLowerCase().includes('guidance') || $('Process Section Response').item.json.section_type?.toLowerCase().includes('financial') || $('Process Section Response').item.json.section_type?.toLowerCase().includes('segment') ? 0 : 2) }}" }, "id": "64f5b8bf-2dd3-4f74-bdd6-669fc0a41799", "name": "Route by Section Type", "type": "n8n-nodes-base.switch", "typeVersion": 3, "position": [ -224, 128 ] }, { "parameters": { "jsCode": "const response = $input.first().json;\nconst sectionCtx = $('Process Section Response').item.json;\nconst rawText = response.choices?.[0]?.message?.content || '{}';\nlet parsed;\ntry {\n const clean = rawText.replace(/```json|```/g, '').trim();\n parsed = JSON.parse(clean);\n} catch(e) {\n return [{ json: { guidance_signals: [], parse_error: e.message } }];\n}\nconst runLog = {\n earnings_call_id: sectionCtx.earnings_call_id,\n run_type: 'guidance_extract',\n model_used: 'llama-3.3-70b-versatile',\n prompt_tokens: response.usage?.prompt_tokens || 0,\n completion_tokens: response.usage?.completion_tokens || 0,\n success: true,\n raw_llm_response: rawText\n};\nconst signals = (parsed.guidance_signals || []).map((g, idx) => ({\n ...g,\n earnings_call_id: sectionCtx.earnings_call_id,\n claim_id: g.claim_id || `${sectionCtx.ticker}-${sectionCtx.quarter_slug}-G${String(idx+1).padStart(3,'0')}`,\n schema_valid: !!g.direction && !!g.transcript_citation && !!g.claim_text,\n validation_errors: [\n !g.direction && 'direction is required',\n !g.transcript_citation && 'transcript_citation is required',\n !g.claim_text && 'claim_text is required'\n ].filter(Boolean),\n falsification_flag: g.falsification_flag || !g.direction || !g.transcript_citation || (g.direction_confidence || 0) < 0.5,\n run_log: runLog\n}));\nreturn signals.length > 0 \n ? signals.map(s => ({ json: s }))\n : [{ json: { guidance_signals_empty: true, earnings_call_id: sectionCtx.earnings_call_id } }];" }, "id": "f5faa609-1590-4552-9921-4b580a01fc76", "name": "Process Guidance Response", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 224, 0 ] }, { "parameters": { "jsCode": "const response = $input.first().json;\nconst sectionCtx = $('Process Section Response').item.json;\n\nconst rawText = response.choices?.[0]?.message?.content || '{}';\nlet parsed;\ntry {\n const clean = rawText.replace(/```json|```/g, '').trim();\n parsed = JSON.parse(clean);\n} catch(e) {\n return [{ json: { risk_admissions: [], parse_error: e.message } }];\n}\n\nconst runLog = {\n earnings_call_id: sectionCtx.earnings_call_id,\n run_type: 'risk_extract',\n model_used: 'claude-opus-4-6',\n prompt_tokens: response.usage?.input_tokens || 0,\n completion_tokens: response.usage?.output_tokens || 0,\n success: true\n};\n\nconst risks = (parsed.risk_admissions || []).map((r, idx) => ({\n ...r,\n earnings_call_id: sectionCtx.earnings_call_id,\n claim_id: r.claim_id || `${sectionCtx.ticker}-${sectionCtx.quarter_slug}-R${String(idx+1).padStart(3,'0')}`,\n schema_valid: !!r.risk_category && !!r.transcript_citation && !!r.severity,\n run_log: runLog\n}));\n\nreturn risks.length > 0\n ? risks.map(r => ({ json: r }))\n : [{ json: { risk_admissions_empty: true, earnings_call_id: sectionCtx.earnings_call_id } }];" }, "id": "1c55cf86-80cf-4e30-9169-32021cdc829c", "name": "Process Risk Response", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 224, 160 ] }, { "parameters": { "jsCode": "const response = $input.first().json;\nconst sectionCtx = $('Process Section Response').item.json;\n\nconst rawText = response.content?.[0]?.text || '{}';\nlet parsed;\ntry {\n const clean = rawText.replace(/```json|```/g, '').trim();\n parsed = JSON.parse(clean);\n} catch(e) {\n return [{ json: { qa_pressure_map: [], parse_error: e.message } }];\n}\n\nconst runLog = {\n earnings_call_id: sectionCtx.earnings_call_id,\n run_type: 'qa_map',\n model_used: 'claude-opus-4-6',\n prompt_tokens: response.usage?.input_tokens || 0,\n completion_tokens: response.usage?.output_tokens || 0,\n success: true\n};\n\nconst qaItems = (parsed.qa_pressure_map || []).map(q => ({\n ...q,\n earnings_call_id: sectionCtx.earnings_call_id,\n schema_valid: !!q.question_topic && !!q.response_type,\n // Clamp pressure score\n pressure_score: Math.min(10, Math.max(1, q.pressure_score || 5)),\n run_log: runLog\n}));\n\nreturn qaItems.length > 0\n ? qaItems.map(q => ({ json: q }))\n : [{ json: { qa_empty: true, earnings_call_id: sectionCtx.earnings_call_id } }];" }, "id": "be982430-c6fc-44da-92f8-3eee6718ea12", "name": "Process QA Response", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 224, 320 ] }, { "parameters": { "operation": "executeQuery", "query": "INSERT INTO guidance_signals (\n earnings_call_id, claim_id, claim_type, claim_text, claim_summary,\n direction, direction_confidence, change_description,\n transcript_citation, citation_speaker, citation_section,\n metric_name, metric_value_current, metric_value_prior, metric_unit, metric_period,\n schema_valid, validation_errors, falsification_flag, falsification_reason\n)\nSELECT\n '{{ $json.earnings_call_id }}'::UUID,\n '{{ $json.claim_id }}',\n '{{ $json.claim_type || \"guidance\" }}',\n '{{ $json.claim_text || \"\" }}',\n '{{ $json.claim_summary || \"\" }}',\n '{{ $json.direction || \"unchanged\" }}',\n {{ $json.direction_confidence || 0 }},\n '{{ $json.change_description || \"\" }}',\n '{{ $json.transcript_citation || \"\" }}',\n '{{ $json.citation_speaker || \"\" }}',\n '{{ $json.citation_section || \"prepared_remarks\" }}',\n NULL, NULL, NULL, NULL, NULL,\n {{ $json.schema_valid || false }},\n '[]'::JSONB,\n {{ $json.falsification_flag || false }},\n NULL\nWHERE '{{ $json.claim_id }}' != 'undefined' AND '{{ $json.guidance_signals_empty }}' != 'true'\nON CONFLICT (claim_id) DO UPDATE\n SET direction = EXCLUDED.direction,\n direction_confidence = EXCLUDED.direction_confidence,\n transcript_citation = EXCLUDED.transcript_citation\nRETURNING id, claim_id, direction, falsification_flag;", "options": {} }, "id": "a7bac940-1257-4dff-b8bb-85e4df17761b", "name": "DB: Insert guidance_signal", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ 448, 0 ] }, { "parameters": { "operation": "executeQuery", "query": "INSERT INTO risk_admissions (\n earnings_call_id, claim_id, risk_category, risk_text, risk_summary,\n severity, uncertainty_language, transcript_citation, citation_speaker,\n is_new_risk, schema_valid\n) VALUES (\n '{{ $json.earnings_call_id }}'::UUID,\n '{{ $json.claim_id }}',\n '{{ $json.risk_category || \"operational\" }}',\n '{{ $json.risk_text }}',\n '{{ $json.risk_summary || \"\" }}',\n '{{ $json.severity || \"low\" }}',\n ARRAY[]::TEXT[],\n '{{ $json.transcript_citation }}',\n '{{ $json.citation_speaker || \"\" }}',\n {{ $json.is_new_risk !== false }},\n {{ $json.schema_valid || false }}\n)\nON CONFLICT (claim_id) DO NOTHING\nRETURNING id, claim_id, severity;", "options": {} }, "id": "bc01a092-af44-4afa-95c2-038efcd78fc9", "name": "DB: Insert risk_admission", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ 448, 160 ] }, { "parameters": { "operation": "executeQuery", "query": "INSERT INTO qa_pressure_map (\n earnings_call_id, question_topic, question_text,\n analyst_name, analyst_firm, times_asked, asked_by_firms,\n response_type, response_text, response_summary,\n is_repeated_topic, pressure_score, schema_valid\n) VALUES (\n '{{ $json.earnings_call_id }}'::UUID,\n '{{ $json.question_topic || \"General\" }}',\n '{{ $json.question_text || \"\" }}',\n '{{ $json.analyst_name || \"\" }}',\n '{{ $json.analyst_firm || \"\" }}',\n {{ $json.times_asked || 1 }},\n ARRAY[]::TEXT[],\n '{{ $json.response_type || \"answered\" }}',\n '{{ $json.response_text || \"\" }}',\n '{{ $json.response_summary || \"\" }}',\n {{ $json.is_repeated_topic || false }},\n {{ $json.pressure_score || 5 }},\n false\n)\nRETURNING id, question_topic, pressure_score;", "options": {} }, "id": "051e79c0-d19a-4e4a-a0c6-d5ec32183f44", "name": "DB: Insert qa_pressure", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ 448, 320 ] }, { "parameters": { "operation": "executeQuery", "query": "INSERT INTO agent_run_log (earnings_call_id, run_type, model_used, prompt_tokens, completion_tokens, success)\nVALUES (\n '{{ $('Set Call Context').first().json.earnings_call_id }}'::UUID,\n 'risk_extract',\n 'llama-3.3-70b-versatile',\n 0,\n 0,\n true\n);", "options": {} }, "id": "2c8b2e6e-181c-4889-bb6d-e2ebc0bb1c64", "name": "DB: Log Agent Run", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ 672, 160 ] }, { "parameters": { "operation": "executeQuery", "query": "SELECT \n ec.id as earnings_call_id,\n ec.company_name,\n ec.ticker,\n ec.fiscal_quarter,\n json_agg(DISTINCT jsonb_build_object(\n 'claim_id', gs.claim_id,\n 'claim_summary', gs.claim_summary,\n 'direction', gs.direction,\n 'direction_confidence', gs.direction_confidence,\n 'change_description', gs.change_description,\n 'metric_name', gs.metric_name,\n 'metric_value_current', gs.metric_value_current,\n 'falsification_flag', gs.falsification_flag\n )) FILTER (WHERE gs.id IS NOT NULL) as guidance_signals,\n json_agg(DISTINCT jsonb_build_object(\n 'claim_id', ra.claim_id,\n 'risk_category', ra.risk_category,\n 'risk_summary', ra.risk_summary,\n 'severity', ra.severity,\n 'is_new_risk', ra.is_new_risk\n )) FILTER (WHERE ra.id IS NOT NULL) as risk_admissions,\n json_agg(DISTINCT jsonb_build_object(\n 'question_topic', qa.question_topic,\n 'times_asked', qa.times_asked,\n 'response_type', qa.response_type,\n 'pressure_score', qa.pressure_score\n )) FILTER (WHERE qa.id IS NOT NULL) as qa_pressure_map\nFROM earnings_calls ec\nLEFT JOIN guidance_signals gs ON gs.earnings_call_id = ec.id\nLEFT JOIN risk_admissions ra ON ra.earnings_call_id = ec.id\nLEFT JOIN qa_pressure_map qa ON qa.earnings_call_id = ec.id\nWHERE ec.id = '{{ $('Set Call Context').first().json.earnings_call_id }}'::UUID\nGROUP BY ec.id, ec.company_name, ec.ticker, ec.fiscal_quarter;", "options": {} }, "id": "ff082563-ec77-452e-b3b6-54f8c66dbfa6", "name": "Fetch All Signals for Summary", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ 672, 0 ] }, { "parameters": { "jsCode": "const response = $input.first().json;\nconst callCtx = $('Set Call Context').first().json;\nconst aggData = $('Fetch All Signals for Summary').first().json;\nconst rawText = response.choices?.[0]?.message?.content || '{}';\nlet parsed;\ntry {\n const clean = rawText.replace(/```json|```/g, '').trim();\n parsed = JSON.parse(clean);\n} catch(e) {\n parsed = {\n overall_tone: 'neutral',\n tone_confidence: 0,\n what_changed: 'Summary generation failed',\n what_didnt_change: '',\n narrative_summary: 'Summary generation failed: ' + e.message\n };\n}\n\n// Group guidance by direction\nconst guidance = aggData.guidance_signals || [];\nconst groupByDir = (dir) => guidance.filter(g => g.direction === dir).map(g => g.claim_id);\n\nreturn [{\n json: {\n earnings_call_id: callCtx.earnings_call_id,\n guidance_strengthened: JSON.stringify(groupByDir('strengthened')),\n guidance_weakened: JSON.stringify(groupByDir('weakened')),\n guidance_unchanged: JSON.stringify(groupByDir('unchanged')),\n new_signals: JSON.stringify(groupByDir('new')),\n retracted_signals: JSON.stringify(groupByDir('retracted')),\n top_pressure_topics: JSON.stringify(parsed.top_pressure_topics || []),\n new_risks: JSON.stringify((aggData.risk_admissions || []).filter(r => r.is_new_risk).map(r => r.claim_id)),\n overall_tone: parsed.overall_tone || 'neutral',\n tone_confidence: parsed.tone_confidence || 0,\n narrative_summary: parsed.narrative_summary || '',\n what_changed: parsed.what_changed || '',\n what_didnt_change: parsed.what_didnt_change || '',\n contradiction_flags: JSON.stringify(parsed.contradiction_flags || []),\n schema_valid: !!parsed.narrative_summary && !!parsed.overall_tone,\n decision_grade_signals: parsed.decision_grade_signals || []\n }\n}];" }, "id": "6cc2afed-911a-4e13-8ebc-1f2e7cccf5e6", "name": "Process Summary Response", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1104, 0 ] }, { "parameters": { "operation": "executeQuery", "query": "INSERT INTO call_summaries (\n earnings_call_id, guidance_strengthened, guidance_weakened,\n guidance_unchanged, new_signals, retracted_signals,\n top_pressure_topics, new_risks, overall_tone, tone_confidence,\n narrative_summary, what_changed, what_didnt_change,\n contradiction_flags, schema_valid\n) VALUES (\n '{{ $json.earnings_call_id }}'::UUID,\n '[]'::JSONB,\n '[]'::JSONB,\n '[]'::JSONB,\n '[]'::JSONB,\n '[]'::JSONB,\n '[]'::JSONB,\n '[]'::JSONB,\n '{{ $json.overall_tone || \"neutral\" }}',\n {{ $json.tone_confidence || 0 }},\n 'Summary generated',\n 'See narrative_summary field',\n 'See narrative_summary field',\n '[]'::JSONB,\n false\n)\nON CONFLICT (earnings_call_id) DO UPDATE SET\n overall_tone = EXCLUDED.overall_tone,\n schema_valid = EXCLUDED.schema_valid\nRETURNING id, earnings_call_id, overall_tone;", "options": {} }, "id": "6c1f1899-faeb-4923-b1dc-9e8be5977aef", "name": "DB: Insert call_summary", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ 1328, 0 ] }, { "parameters": { "operation": "executeQuery", "query": "UPDATE earnings_calls SET \n processing_status = 'complete',\n updated_at = NOW()\nWHERE id = '{{ $json.earnings_call_id }}'::UUID\nRETURNING id, company_name, ticker, fiscal_quarter, processing_status;", "options": {} }, "id": "30a4382b-d20b-4e8e-89d7-7f01de270e0b", "name": "DB: Mark Call Complete", "type": "n8n-nodes-base.postgres", "typeVersion": 2.5, "position": [ 1552, 0 ] }, { "parameters": { "jsCode": "const callResult = $input.first().json;\nconst summaryData = $('Process Summary Response').first().json;\n\n// Falsification check\nconst falsificationFailed = summaryData.guidance_strengthened === '[]' &&\n summaryData.guidance_weakened === '[]' &&\n summaryData.guidance_unchanged === '[]' &&\n summaryData.new_signals === '[]';\n\nreturn [{\n json: {\n success: true,\n earnings_call_id: callResult.id,\n company: callResult.company_name,\n ticker: callResult.ticker,\n quarter: callResult.fiscal_quarter,\n status: callResult.processing_status,\n overall_tone: summaryData.overall_tone,\n narrative_summary: summaryData.narrative_summary,\n what_changed: summaryData.what_changed,\n decision_grade_signals: summaryData.decision_grade_signals,\n falsification_warning: falsificationFailed ? 'WARNING: No guidance signals extracted — schema may need redesign' : null,\n schema_valid: summaryData.schema_valid\n }\n}];" }, "id": "eea3db56-7843-4cbd-8140-51b7ec183a85", "name": "Final Response", "type": "n8n-nodes-base.code", "typeVersion": 2, "position": [ 1760, 0 ] }, { "parameters": { "respondWith": "json", "responseBody": "={{ JSON.stringify($json) }}", "options": { "responseCode": 200 } }, "id": "68f0d9aa-6753-4eba-a8b1-d0af58501dca", "name": "Webhook Response", "type": "n8n-nodes-base.respondToWebhook", "typeVersion": 1, "position": [ 1984, 0 ] }, { "parameters": { "method": "POST", "url": "https://api.groq.com/openai/v1/chat/completions", "authentication": "predefinedCredentialType", "nodeCredentialType": "groqApi", "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={\n \"model\": \"llama-3.3-70b-versatile\",\n \"temperature\": 0.1,\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You must return ONLY raw JSON. No markdown, no backticks, no explanation. Start with { and end with }. You are a senior investment analyst writing a structured call summary for Mycroft.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Generate a structured call summary.\\n\\nCOMPANY: {{ $json.company_name }} | TICKER: {{ $json.ticker }} | QUARTER: {{ $json.fiscal_quarter }}\\n\\nReturn ONLY this JSON:\\n{\\\"overall_tone\\\":\\\"bullish\\\",\\\"tone_confidence\\\":0.8,\\\"what_changed\\\":\\\"narrative here\\\",\\\"what_didnt_change\\\":\\\"narrative here\\\",\\\"narrative_summary\\\":\\\"4-6 sentence summary\\\",\\\"top_pressure_topics\\\":[],\\\"contradiction_flags\\\":[],\\\"decision_grade_signals\\\":[]}\"\n }\n ]\n}", "options": { "timeout": 120000 } }, "id": "595c119d-15e0-40be-b01f-9093904864d2", "name": "Groq: Generate Call Summary", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 880, 0 ] }, { "parameters": { "method": "POST", "url": "https://api.groq.com/openai/v1/chat/completions", "authentication": "predefinedCredentialType", "nodeCredentialType": "groqApi", "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={\n \"model\": \"llama-3.3-70b-versatile\",\n \"temperature\": 0.1,\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You must return ONLY raw JSON. No markdown, no asterisks, no explanation. Start your response directly with { and end with }. Any other format will cause a system failure. You are a financial transcript parser for Mycroft. Split the earnings call transcript into labeled sections.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"... same user prompt as before ...\"\n }\n ]\n}", "options": { "timeout": 120000 } }, "id": "c3338d53-e5ce-4f08-8039-365eda5c12cb", "name": "Groq: Parse Transcript Sections", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ -880, 128 ] }, { "parameters": { "method": "POST", "url": "https://api.groq.com/openai/v1/chat/completions", "authentication": "predefinedCredentialType", "nodeCredentialType": "groqApi", "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={\n \"model\": \"llama-3.3-70b-versatile\",\n \"temperature\": 0.1,\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You are a financial analyst. You must return ONLY raw JSON. No markdown, no backticks, no explanation. Start with { and end with }.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Read this earnings call section and extract every forward-looking statement about revenue, margins, EPS, growth, capex, or guidance.\\n\\nCOMPANY: {{ $json.company_name }} | TICKER: {{ $json.ticker }} | QUARTER: {{ $json.fiscal_quarter }}\\n\\nSECTION TEXT:\\n{{ $json.content || $json.section_text }}\\n\\nFor each guidance statement found, classify direction as: strengthened | weakened | unchanged | new | retracted\\n\\nReturn this exact JSON structure:\\n{\\\"guidance_signals\\\":[{\\\"claim_id\\\":\\\"TICKER-QUARTER-G001\\\",\\\"claim_type\\\":\\\"guidance\\\",\\\"claim_text\\\":\\\"exact quote from text\\\",\\\"claim_summary\\\":\\\"one sentence summary\\\",\\\"direction\\\":\\\"strengthened\\\",\\\"direction_confidence\\\":0.9,\\\"change_description\\\":\\\"what changed\\\",\\\"transcript_citation\\\":\\\"exact quote\\\",\\\"citation_speaker\\\":\\\"speaker name\\\",\\\"citation_section\\\":\\\"prepared_remarks\\\",\\\"metric_name\\\":\\\"revenue\\\",\\\"metric_value_current\\\":400,\\\"metric_value_prior\\\":380,\\\"metric_unit\\\":\\\"billion USD\\\",\\\"metric_period\\\":\\\"FY2024\\\",\\\"falsification_flag\\\":false,\\\"falsification_reason\\\":null}]}\"\n }\n ]\n}", "options": { "timeout": 120000 } }, "id": "d47b2cf0-6fdf-438b-b5d8-48030a0a577b", "name": "Groq: Extract Guidance Signals", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 0, 0 ] }, { "parameters": { "method": "POST", "url": "https://api.groq.com/openai/v1/chat/completions", "authentication": "predefinedCredentialType", "nodeCredentialType": "groqApi", "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={\n \"model\": \"llama-3.3-70b-versatile\",\n \"temperature\": 0.1,\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You must return ONLY raw JSON. No markdown, no backticks, no explanation. Start with { and end with }. You are a financial risk analyst extracting risk admissions for Mycroft.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Extract all risk admissions and uncertainty language.\\n\\nCategories: macro | competitive | regulatory | operational | financial\\nSeverity: critical | high | medium | low\\n\\nCOMPANY: {{ $json.company_name }} | QUARTER: {{ $json.fiscal_quarter }}\\n\\nReturn ONLY this JSON:\\n{\\\"risk_admissions\\\":[{\\\"claim_id\\\":\\\"{{ $json.ticker }}-{{ $json.quarter_slug }}-R001\\\",\\\"risk_category\\\":\\\"macro\\\",\\\"risk_text\\\":\\\"...\\\",\\\"risk_summary\\\":\\\"...\\\",\\\"severity\\\":\\\"medium\\\",\\\"uncertainty_language\\\":[\\\"may\\\",\\\"could\\\"],\\\"transcript_citation\\\":\\\"...\\\",\\\"citation_speaker\\\":\\\"...\\\",\\\"is_new_risk\\\":true}]}\\n\\nSECTION TEXT:\\n{{ $json.content || $json.section_text }}\"\n }\n ]\n}", "options": { "timeout": 90000 } }, "id": "b42ac5b4-421c-43f4-a6d1-aaada5c964ef", "name": "Groq: Extract Risk Admissions", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 0, 160 ] }, { "parameters": { "method": "POST", "url": "https://api.groq.com/openai/v1/chat/completions", "authentication": "predefinedCredentialType", "nodeCredentialType": "groqApi", "sendBody": true, "contentType": "raw", "rawContentType": "application/json", "body": "={\n \"model\": \"llama-3.3-70b-versatile\",\n \"temperature\": 0.1,\n \"messages\": [\n {\n \"role\": \"system\",\n \"content\": \"You must return ONLY raw JSON. No markdown, no backticks, no explanation. Start with { and end with }. You analyze Q&A sections of earnings calls for Mycroft.\"\n },\n {\n \"role\": \"user\",\n \"content\": \"Analyze this Q&A section. Group by topic, classify response, score pressure 1-10.\\n\\nResponse types: answered | deflected | deferred | partial | acknowledged\\nPressure: 1-3 single analyst answered | 4-6 multiple or partial | 7-10 repeated and deflected\\n\\nCOMPANY: {{ $json.company_name }} | QUARTER: {{ $json.fiscal_quarter }}\\n\\nReturn ONLY this JSON:\\n{\\\"qa_pressure_map\\\":[{\\\"question_topic\\\":\\\"...\\\",\\\"question_text\\\":\\\"...\\\",\\\"analyst_name\\\":\\\"...\\\",\\\"analyst_firm\\\":\\\"...\\\",\\\"times_asked\\\":1,\\\"asked_by_firms\\\":[\\\"firm1\\\"],\\\"response_type\\\":\\\"answered\\\",\\\"response_text\\\":\\\"...\\\",\\\"response_summary\\\":\\\"...\\\",\\\"is_repeated_topic\\\":false,\\\"pressure_score\\\":5}]}\\n\\nQA SECTION TEXT:\\n{{ $json.content || $json.section_text }}\"\n }\n ]\n}", "options": { "timeout": 90000 } }, "id": "15e2b248-ef2f-45fb-a296-659a83af57d5", "name": "Groq: Map QA Pressure", "type": "n8n-nodes-base.httpRequest", "typeVersion": 4.2, "position": [ 0, 320 ] }, { "parameters": { "operation": "executeQuery", "query": "-- ============================================================\n-- MYCROFT: Earnings Call Intelligence Agent\n-- PostgreSQL Schema\n-- ============================================================\n\n-- Enable UUID generation\nCREATE EXTENSION IF NOT EXISTS \"uuid-ossp\";\n\n-- ============================================================\n-- TABLE 1: earnings_calls\n-- Master record for each processed transcript\n-- ============================================================\nCREATE TABLE IF NOT EXISTS earnings_calls (\n id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n company_name VARCHAR(255) NOT NULL,\n ticker VARCHAR(20) NOT NULL,\n call_date DATE NOT NULL,\n fiscal_quarter VARCHAR(10), -- e.g. \"Q3 2024\"\n fiscal_year INTEGER,\n call_type VARCHAR(50) DEFAULT 'quarterly', -- quarterly | annual | special\n raw_transcript TEXT NOT NULL,\n transcript_source VARCHAR(255), -- manual | api | scraped\n word_count INTEGER,\n processing_status VARCHAR(50) DEFAULT 'pending', -- pending | processing | complete | failed\n processing_error TEXT,\n created_at TIMESTAMPTZ DEFAULT NOW(),\n updated_at TIMESTAMPTZ DEFAULT NOW()\n);\n\nCREATE INDEX idx_earnings_calls_ticker ON earnings_calls(ticker);\nCREATE INDEX idx_earnings_calls_call_date ON earnings_calls(call_date);\nCREATE INDEX idx_earnings_calls_status ON earnings_calls(processing_status);\n\n\n-- ============================================================\n-- TABLE 2: transcript_sections\n-- Parsed sections of the transcript (CEO / CFO / QA / Other)\n-- ============================================================\nCREATE TABLE IF NOT EXISTS transcript_sections (\n id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n earnings_call_id UUID NOT NULL REFERENCES earnings_calls(id) ON DELETE CASCADE,\n section_type VARCHAR(50) NOT NULL, -- prepared_remarks | qa | opening | closing\n speaker_name VARCHAR(255),\n speaker_role VARCHAR(255), -- CEO | CFO | Analyst | Moderator\n speaker_firm VARCHAR(255), -- for analyst Q&A\n section_text TEXT NOT NULL,\n section_order INTEGER,\n char_start INTEGER, -- character offset in raw transcript\n char_end INTEGER,\n created_at TIMESTAMPTZ DEFAULT NOW()\n);\n\nCREATE INDEX idx_sections_call_id ON transcript_sections(earnings_call_id);\nCREATE INDEX idx_sections_type ON transcript_sections(section_type);\n\n\n-- ============================================================\n-- TABLE 3: guidance_signals\n-- Extracted management guidance statements (shared claims schema)\n-- ============================================================\nCREATE TABLE IF NOT EXISTS guidance_signals (\n id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n earnings_call_id UUID NOT NULL REFERENCES earnings_calls(id) ON DELETE CASCADE,\n section_id UUID REFERENCES transcript_sections(id),\n\n -- Shared Claims Schema Fields\n claim_id VARCHAR(50) UNIQUE NOT NULL, -- e.g. AAPL-Q3-2024-G001\n claim_type VARCHAR(50) NOT NULL, -- guidance | risk | outlook | metric\n claim_text TEXT NOT NULL, -- verbatim or near-verbatim\n claim_summary TEXT, -- 1-sentence normalized summary\n\n -- Guidance Direction (FALSIFICATION TARGET)\n direction VARCHAR(20) NOT NULL -- strengthened | unchanged | weakened | new | retracted\n CHECK (direction IN ('strengthened','unchanged','weakened','new','retracted')),\n direction_confidence NUMERIC(3,2) -- 0.00 to 1.00\n CHECK (direction_confidence >= 0 AND direction_confidence <= 1),\n\n -- Prior Call Comparison\n prior_call_id UUID REFERENCES earnings_calls(id),\n prior_claim_text TEXT, -- what was said last quarter\n change_description TEXT, -- explicit diff narrative\n\n -- Supporting Evidence\n transcript_citation TEXT NOT NULL, -- exact quote from transcript\n citation_speaker VARCHAR(255),\n citation_section VARCHAR(50),\n\n -- Metric Extraction (if quantitative)\n metric_name VARCHAR(255), -- \"Revenue guidance\" | \"EPS range\"\n metric_value_current NUMERIC,\n metric_value_prior NUMERIC,\n metric_unit VARCHAR(50), -- \"$B\" | \"%\" | \"units\"\n metric_period VARCHAR(50), -- \"FY2025\" | \"Q4 2024\"\n\n -- Schema Validity\n schema_valid BOOLEAN DEFAULT FALSE,\n validation_errors JSONB,\n falsification_flag BOOLEAN DEFAULT FALSE, -- true if direction is null or uncited\n falsification_reason TEXT,\n\n created_at TIMESTAMPTZ DEFAULT NOW()\n);\n\nCREATE INDEX idx_guidance_call_id ON guidance_signals(earnings_call_id);\nCREATE INDEX idx_guidance_direction ON guidance_signals(direction);\nCREATE INDEX idx_guidance_ticker ON guidance_signals(claim_id);\nCREATE INDEX idx_guidance_flagged ON guidance_signals(falsification_flag);\n\n\n-- ============================================================\n-- TABLE 4: risk_admissions\n-- Structured risk language extracted from transcript\n-- ============================================================\nCREATE TABLE IF NOT EXISTS risk_admissions (\n id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n earnings_call_id UUID NOT NULL REFERENCES earnings_calls(id) ON DELETE CASCADE,\n section_id UUID REFERENCES transcript_sections(id),\n\n claim_id VARCHAR(50) UNIQUE NOT NULL, -- e.g. AAPL-Q3-2024-R001\n risk_category VARCHAR(100), -- macro | competitive | regulatory | operational | financial\n risk_text TEXT NOT NULL,\n risk_summary TEXT,\n severity VARCHAR(20) -- low | medium | high | critical\n CHECK (severity IN ('low','medium','high','critical')),\n uncertainty_language TEXT[], -- array of hedging phrases found\n transcript_citation TEXT NOT NULL,\n citation_speaker VARCHAR(255),\n\n -- Is this new vs. previously disclosed?\n is_new_risk BOOLEAN,\n prior_disclosure_call UUID REFERENCES earnings_calls(id),\n\n schema_valid BOOLEAN DEFAULT FALSE,\n created_at TIMESTAMPTZ DEFAULT NOW()\n);\n\nCREATE INDEX idx_risk_call_id ON risk_admissions(earnings_call_id);\nCREATE INDEX idx_risk_category ON risk_admissions(risk_category);\nCREATE INDEX idx_risk_severity ON risk_admissions(severity);\n\n\n-- ============================================================\n-- TABLE 5: qa_pressure_map\n-- Analyst question patterns and management response behavior\n-- ============================================================\nCREATE TABLE IF NOT EXISTS qa_pressure_map (\n id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n earnings_call_id UUID NOT NULL REFERENCES earnings_calls(id) ON DELETE CASCADE,\n section_id UUID REFERENCES transcript_sections(id),\n\n question_topic VARCHAR(255) NOT NULL,\n question_text TEXT,\n analyst_name VARCHAR(255),\n analyst_firm VARCHAR(255),\n times_asked INTEGER DEFAULT 1, -- how many analysts asked this topic\n asked_by_firms TEXT[], -- array of analyst firms\n\n -- Response classification\n response_type VARCHAR(50) -- answered | deflected | deferred | partial | acknowledged\n CHECK (response_type IN ('answered','deflected','deferred','partial','acknowledged')),\n response_text TEXT,\n response_summary TEXT,\n\n -- Pressure signal\n is_repeated_topic BOOLEAN DEFAULT FALSE, -- asked in prior call too?\n prior_call_response VARCHAR(50), -- how it was answered last time\n pressure_score INTEGER -- 1-10, derived from repetition + analyst tier\n CHECK (pressure_score BETWEEN 1 AND 10),\n\n schema_valid BOOLEAN DEFAULT FALSE,\n created_at TIMESTAMPTZ DEFAULT NOW()\n);\n\nCREATE INDEX idx_qa_call_id ON qa_pressure_map(earnings_call_id);\nCREATE INDEX idx_qa_topic ON qa_pressure_map(question_topic);\nCREATE INDEX idx_qa_response_type ON qa_pressure_map(response_type);\nCREATE INDEX idx_qa_pressure ON qa_pressure_map(pressure_score);\n\n\n-- ============================================================\n-- TABLE 6: call_summaries\n-- Final \"What Changed / What Didn't\" roll-up per call\n-- ============================================================\nCREATE TABLE IF NOT EXISTS call_summaries (\n id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n earnings_call_id UUID UNIQUE NOT NULL REFERENCES earnings_calls(id) ON DELETE CASCADE,\n\n -- Structured delta summary\n guidance_strengthened JSONB, -- array of claim_ids that strengthened\n guidance_weakened JSONB, -- array of claim_ids that weakened\n guidance_unchanged JSONB, -- array of claim_ids unchanged\n new_signals JSONB, -- array of claim_ids that are new this quarter\n retracted_signals JSONB, -- array of claim_ids retracted vs prior\n\n -- Top pressure topics from QA\n top_pressure_topics JSONB, -- [{topic, times_asked, response_type}]\n\n -- New risks this call\n new_risks JSONB, -- array of risk_admission claim_ids\n\n -- Overall call tone\n overall_tone VARCHAR(50), -- bullish | neutral | cautious | defensive\n tone_confidence NUMERIC(3,2),\n\n -- Contradiction flags for Resolver Agent\n contradiction_flags JSONB, -- pre-computed flags for Resolver Agent\n\n -- Full narrative summary\n narrative_summary TEXT,\n what_changed TEXT,\n what_didnt_change TEXT,\n\n schema_valid BOOLEAN DEFAULT FALSE,\n generated_at TIMESTAMPTZ DEFAULT NOW()\n);\n\n\n-- ============================================================\n-- TABLE 7: agent_run_log\n-- Audit trail for every agent execution\n-- ============================================================\nCREATE TABLE IF NOT EXISTS agent_run_log (\n id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),\n earnings_call_id UUID REFERENCES earnings_calls(id),\n run_type VARCHAR(100), -- section_parse | guidance_extract | risk_extract | qa_map | summary\n model_used VARCHAR(100),\n prompt_tokens INTEGER,\n completion_tokens INTEGER,\n latency_ms INTEGER,\n success BOOLEAN,\n error_message TEXT,\n raw_llm_response TEXT,\n created_at TIMESTAMPTZ DEFAULT NOW()\n);\n\nCREATE INDEX idx_runlog_call_id ON agent_run_log(earnings_call_id);\nCREATE INDEX idx_runlog_success ON agent_run_log(success);\n\n\n-- ============================================================\n-- HELPER: auto-update updated_at on earnings_calls\n-- ============================================================\nCREATE OR REPLACE FUNCTION update_updated_at_column()\nRETURNS TRIGGER AS $$\nBEGIN\n NEW.updated_at = NOW();\n RETURN NEW;\nEND;\n$$ LANGUAGE plpgsql;\n\nCREATE TRIGGER trg_earnings_calls_updated_at\n BEFORE UPDATE ON earnings_calls\n FOR EACH ROW EXECUTE FUNCTION update_updated_at_column();", "options": {} }, "type": "n8n-nodes-base.postgres", "typeVersion": 2.6, "position": [ -1824, -80 ], "id": "83eeda2d-4004-4c95-9e36-da37e8596692", "name": "Execute a SQL query", "disabled": true }, { "id": "4a5f5314-eedb-5c02-a3cd-83da12e951e4", "name": "Publication · Overview and setup", "type": "n8n-nodes-base.stickyNote", "typeVersion": 1, "position": [ -2624, -80 ], "parameters": { "content": "# My workflow 7\n\n## Purpose and structure\nThis folder contains the **My workflow 7** workflow. Its executable nodes use `code`, `httpRequest`, `postgres`, `respondToWebhook`, `set`, `switch`, `webhook`. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.\n\n## Setup\nImport inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.\n\n## Entry points\nWebhook: Receive Transcript\n\n## Verification\nSanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.\n\n## Attribution\nNik Bear Brown; rights confirmed 2026-10-19\nMIT; preserve source notices.", "width": 700, "height": 800, "color": 1 } } ], "connections": { "Webhook: Receive Transcript": { "main": [ [ { "node": "Validate Input", "type": "main", "index": 0 } ] ] }, "Validate Input": { "main": [ [ { "node": "DB: Insert earnings_call", "type": "main", "index": 0 } ] ] }, "DB: Insert earnings_call": { "main": [ [ { "node": "Set Call Context", "type": "main", "index": 0 } ] ] }, "Set Call Context": { "main": [ [ { "node": "Groq: Parse Transcript Sections", "type": "main", "index": 0 } ] ] }, "Process Section Response": { "main": [ [ { "node": "DB: Insert transcript_section", "type": "main", "index": 0 } ] ] }, "DB: Insert transcript_section": { "main": [ [ { "node": "Route by Section Type", "type": "main", "index": 0 } ] ] }, "Route by Section Type": { "main": [ [ { "node": "Groq: Extract Guidance Signals", "type": "main", "index": 0 }, { "node": "Groq: Extract Risk Admissions", "type": "main", "index": 0 } ], [ { "node": "Groq: Map QA Pressure", "type": "main", "index": 0 } ], [ { "node": "Groq: Extract Risk Admissions", "type": "main", "index": 0 }, { "node": "Groq: Extract Guidance Signals", "type": "main", "index": 0 } ] ] }, "Process Guidance Response": { "main": [ [ { "node": "DB: Insert guidance_signal", "type": "main", "index": 0 } ] ] }, "Process Risk Response": { "main": [ [ { "node": "DB: Insert risk_admission", "type": "main", "index": 0 } ] ] }, "Process QA Response": { "main": [ [ { "node": "DB: Insert qa_pressure", "type": "main", "index": 0 } ] ] }, "DB: Insert guidance_signal": { "main": [ [ { "node": "DB: Log Agent Run", "type": "main", "index": 0 } ] ] }, "DB: Insert risk_admission": { "main": [ [ { "node": "DB: Log Agent Run", "type": "main", "index": 0 } ] ] }, "DB: Insert qa_pressure": { "main": [ [ { "node": "DB: Log Agent Run", "type": "main", "index": 0 } ] ] }, "DB: Log Agent Run": { "main": [ [ { "node": "Fetch All Signals for Summary", "type": "main", "index": 0 } ] ] }, "Fetch All Signals for Summary": { "main": [ [ { "node": "Groq: Generate Call Summary", "type": "main", "index": 0 } ] ] }, "Process Summary Response": { "main": [ [ { "node": "DB: Insert call_summary", "type": "main", "index": 0 } ] ] }, "DB: Insert call_summary": { "main": [ [ { "node": "DB: Mark Call Complete", "type": "main", "index": 0 } ] ] }, "DB: Mark Call Complete": { "main": [ [ { "node": "Final Response", "type": "main", "index": 0 } ] ] }, "Final Response": { "main": [ [ { "node": "Webhook Response", "type": "main", "index": 0 } ] ] }, "Groq: Generate Call Summary": { "main": [ [ { "node": "Process Summary Response", "type": "main", "index": 0 } ] ] }, "Groq: Parse Transcript Sections": { "main": [ [ { "node": "Process Section Response", "type": "main", "index": 0 } ] ] }, "Groq: Extract Guidance Signals": { "main": [ [ { "node": "Process Guidance Response", "type": "main", "index": 0 } ] ] }, "Groq: Extract Risk Admissions": { "main": [ [ { "node": "Process Risk Response", "type": "main", "index": 0 } ] ] }, "Groq: Map QA Pressure": { "main": [ [ { "node": "Process QA Response", "type": "main", "index": 0 } ] ] } }, "active": false, "settings": { "executionOrder": "v1" } }