/**
 * Agent Session Memory — ~/.careervivid/memory.md
 *
 * Architecture
 * ════════════
 * The memory file has TWO layers:
 *
 *  ┌─────────────────────────────────────────────────────────────────┐
 *  │  LAYER 1 — Knowledge Base (🔒 persisted forever, never deleted) │
 *  │  Structured sections extracted across ALL sessions:             │
 *  │   • Career Goals & Preferences                                  │
 *  │   • Resume State (active IDs, versions, tailoring history)      │
 *  │   • Job Pipeline (tracked companies, statuses, decisions)       │
 *  │   • Skills & Experience Context                                 │
 *  │   • Interview Prep Context                                      │
 *  │   • Cover Letter History                                        │
 *  └─────────────────────────────────────────────────────────────────┘
 *  ┌─────────────────────────────────────────────────────────────────┐
 *  │  LAYER 2 — Recent Session Log (rolling, auto-compacted)         │
 *  │  Last N sessions with full context of what was done.            │
 *  │  When compaction fires, sessions are merged into the            │
 *  │  Knowledge Base above (not discarded).                          │
 *  └─────────────────────────────────────────────────────────────────┘
 *
 * Compaction strategy
 * ───────────────────
 * When total file size > MAX_CHARS:
 *   1. Parse the knowledge base sections
 *   2. Merge each older session's facts INTO the knowledge base (upsert)
 *   3. Drop sessions older than KEEP_SESSIONS, keeping the most recent N
 *   4. Optionally call the LLM (via CV proxy) to produce a true distillation
 *      if an api key is available — this is the "smart" path
 *   5. Write the compacted file back
 *
 * System prompt injection
 * ───────────────────────
 * Only injects the knowledge base + last 2 sessions (≤ PROMPT_INJECT_CHARS).
 * The agent always sees what matters, never sees everything.
 *
 * Public API
 * ──────────
 *  loadMemory()                   → raw file string
 *  buildMemoryBlock()             → string for system prompt injection
 *  saveSessionMemory(opts)        → append + compact
 *  buildSessionSummary(opts)      → build summary string from session data
 *  MEMORY_SECTION                 → static system-prompt header
 */
export interface SessionHighlight {
    tool: string;
    args: string;
    outcome: string;
}
export interface KnowledgeBase {
    /** e.g. ["harness engineering", "AI-first companies", "solutions engineering"] */
    careerGoals: string[];
    /** Preferred role titles */
    targetRoles: string[];
    /** Preferred companies / sectors */
    targetCompanies: string[];
    /** Active resume ID and title */
    activeResume: {
        id: string;
        title: string;
        lastUpdated: string;
    } | null;
    /** All known resume IDs */
    resumeHistory: Array<{
        id: string;
        title: string;
    }>;
    /** Job pipeline entries worth remembering */
    jobPipeline: Array<{
        company: string;
        role: string;
        status: string;
        note?: string;
    }>;
    /** Cover letters generated */
    coverLetters: Array<{
        company: string;
        role: string;
        savedId?: string;
    }>;
    /** Interview prep done */
    interviewPrep: Array<{
        company: string;
        role: string;
        topics: string[];
    }>;
    /** Skills the user has mentioned or had added */
    skills: string[];
    /** Misc facts (work auth, location, salary expectation, etc.) */
    facts: Record<string, string>;
    /** Last updated ISO timestamp */
    updatedAt: string;
}
export declare function loadMemory(): string;
/**
 * Build the system-prompt memory block.
 *
 * Design principle: O(1) token cost regardless of pipeline size.
 *   - 10 jobs  → same output size as 1,000 jobs
 *   - Full details always come from tool calls (tracker_list_jobs, etc.)
 *   - This block is context/orientation, not a data dump
 *
 * Typical output: ~250–400 chars (~65–100 tokens)
 * Hard ceiling:    1,200 chars (~300 tokens) — never exceeded by realistic data
 */
export declare function buildMemoryBlock(): string;
/**
 * Static system-prompt section instructing the agent how to use memory.
 * Imported by instructions.ts.
 */
export declare const MEMORY_SECTION: string;
export interface SessionSummaryInput {
    turns: number;
    mutations: number;
    highlights: SessionHighlight[];
    mode: string;
    model: string;
    careerGoals?: string[];
    targetRoles?: string[];
    targetCompanies?: string[];
    skills?: string[];
    activeResumeId?: string;
    activeResumeTitle?: string;
    jobActions?: Array<{
        company: string;
        role: string;
        status: string;
        note?: string;
    }>;
    coverLetters?: Array<{
        company: string;
        role: string;
        savedId?: string;
    }>;
    interviewPrep?: Array<{
        company: string;
        role: string;
        topics: string[];
    }>;
    facts?: Record<string, string>;
    summary?: string;
}
/**
 * Build a rich session entry block.
 * Returns a markdown string with embedded JSON metadata for later parsing.
 */
export declare function buildSessionSummary(opts: SessionSummaryInput): string;
/**
 * Append a session summary to the memory file, merge into KB, compact if needed.
 */
export declare function saveSessionMemory(opts: SessionSummaryInput): void;
export interface CodingSessionData {
    /** Absolute path of the working directory when the session ended */
    cwd: string;
    /** ISO timestamp of when the session was saved */
    savedAt: string;
    /** Persona mode ("coding", "resume", etc.) */
    mode: string;
    /** Human-readable summary of what happened in the session */
    summary: string;
    /** Files the agent wrote or patched during the session */
    filesChanged: string[];
    /** Short description of the last thing that was built/created */
    lastBuilt: string;
    /** Git branch active during the session (empty if no git repo) */
    branch: string;
}
/**
 * Load the last coding session from ~/.careervivid/coding-session.md.
 * Returns null if the file does not exist or cannot be parsed.
 * Intentionally synchronous — called at startup before the agent loop.
 */
export declare function loadCodingSession(): CodingSessionData | null;
/**
 * Save the current coding session to ~/.careervivid/coding-session.md.
 * Overwrites the previous entry — only the most recent session is kept here.
 * Full history is preserved in memory.md via saveSessionMemory().
 */
export declare function saveCodingSession(data: CodingSessionData): void;
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