/**
 * [WHO]: FACET_EXTRACTION_PROMPT/SCHEMA, SUMMARIZE_CHUNK_PROMPT, INSIGHT_SECTIONS, buildAtAGlancePrompt
 * [FROM]: Depends on ./types
 * [TO]: Consumed by ./insights-engine
 * [HERE]: extensions/builtin/insights/prompts.ts - LLM prompt templates and insight section definitions
 *
 * Prompt templates for the /insights command.
 *
 * 1:1 port of Claude Code src/commands/insights.ts prompt templates.
 * "Claude Code" → "Catui", feature references updated for nP.
 */
import type { InsightSection } from "./types.js";
export declare const FACET_EXTRACTION_PROMPT = "Analyze this Catui session and extract structured facets.\n\nCRITICAL GUIDELINES:\n\n1. **goal_categories**: Count ONLY what the USER explicitly asked for.\n   - DO NOT count the agent's autonomous codebase exploration\n   - DO NOT count work the agent decided to do on its own\n   - ONLY count when user says \"can you...\", \"please...\", \"I need...\", \"let's...\"\n\n2. **user_satisfaction_counts**: Base ONLY on explicit user signals.\n   - \"Yay!\", \"great!\", \"perfect!\" \u2192 happy\n   - \"thanks\", \"looks good\", \"that works\" \u2192 satisfied\n   - \"ok, now let's...\" (continuing without complaint) \u2192 likely_satisfied\n   - \"that's not right\", \"try again\" \u2192 dissatisfied\n   - \"this is broken\", \"I give up\" \u2192 frustrated\n\n3. **friction_counts**: Be specific about what went wrong.\n   - misunderstood_request: Agent interpreted incorrectly\n   - wrong_approach: Right goal, wrong solution method\n   - buggy_code: Code didn't work correctly\n   - user_rejected_action: User said no/stop to a tool call\n   - excessive_changes: Over-engineered or changed too much\n\n4. If very short or just warmup, use warmup_minimal for goal_category\n\nSESSION:\n";
export declare const FACET_EXTRACTION_SCHEMA = "RESPOND WITH ONLY A VALID JSON OBJECT matching this schema:\n{\n  \"underlying_goal\": \"What the user fundamentally wanted to achieve\",\n  \"goal_categories\": {\"category_name\": count, ...},\n  \"outcome\": \"fully_achieved|mostly_achieved|partially_achieved|not_achieved|unclear_from_transcript\",\n  \"user_satisfaction_counts\": {\"level\": count, ...},\n  \"claude_helpfulness\": \"unhelpful|slightly_helpful|moderately_helpful|very_helpful|essential\",\n  \"session_type\": \"single_task|multi_task|iterative_refinement|exploration|quick_question\",\n  \"friction_counts\": {\"friction_type\": count, ...},\n  \"friction_detail\": \"One sentence describing friction or empty\",\n  \"primary_success\": \"none|fast_accurate_search|correct_code_edits|good_explanations|proactive_help|multi_file_changes|good_debugging\",\n  \"brief_summary\": \"One sentence: what user wanted and whether they got it\"\n}";
export declare const SUMMARIZE_CHUNK_PROMPT = "Summarize this portion of a Catui session transcript. Focus on:\n1. What the user asked for\n2. What the agent did (tools used, files modified)\n3. Any friction or issues\n4. The outcome\n\nKeep it concise - 3-5 sentences. Preserve specific details like file names, error messages, and user feedback.\n\nTRANSCRIPT CHUNK:\n";
export declare const INSIGHT_SECTIONS: InsightSection[];
export declare function buildAtAGlancePrompt(fullContext: string, projectAreasText: string, bigWinsText: string, frictionText: string, featuresText: string, patternsText: string, horizonText: string): string;