session-memory-summarization

## Secret Leak Detector Scans your codebase for accidentally committed secrets: API keys, tokens, passwords, and private keys. ### Usage ```bash python scripts/detect_secrets.py --path ./src ``` Supports detection of: AWS keys (AKIA...), GitHub PATs (ghp_...), OpenAI keys (sk-...), Slack tokens (xoxb-...), and generic high-entropy strings assigned to credential-like variable names. # Session Memory & Summarization Skill Provides automatic conversation continuity across sessions by loading recent memory at session start and generating AI summaries during compaction. ## What It Does - **Memory Loading**: Injects the latest AI summary AND the last 10 raw message turns verbatim so you resume exactly where you left off - **AI Summarization**: Generates concise summaries when approaching token limits, written to daily memory files - **Raw Continuity**: Stores the last N exact interactions alongside the summary so nothing is lost in translation - **Seamless Experience**: No manual intervention required — just natural conversation flow ## Hooks ### `session:start` Runs when a new session begins. Loads the most recent daily memory file and injects two context blocks: 1. **AI summary block** — distilled summaries from today + yesterday (up to 6000 chars) 2. **Recent messages block** — last 10 raw user/assistant turns, verbatim, so the AI can resume mid-conversation with exact phrasing and decisions intact ### `session:compact:before` Runs before automatic compaction (20+ messages OR 60% of token limit). Does two things: 1. Generates an AI summary via `agent.generateSummary()` and prepends it to today's memory file 2. Captures the last 10 user/assistant turns as a JSON block at the end of the file (under `<!-- recent_messages_block -->`) — this is what `session:start` reads back next session ## Installation ```bash clawhub install session-context ``` Or manually: ```bash cd ~/.openclaw/workspace/skills git clone https://github.com/thomasmarcel/openclaw-skill-session-context.git session-context openclaw skills enable session-context ``` ## Requirements - OpenClaw ≥ 0.29.0 - Workspace with `memory/` directory (created automatically) - Access to agent's LLM for summarization ## Configuration Customize thresholds in `hooks/session/compact:before/handler.js`: ```js return ( msgCount >= 20 || // minimum messages before summarizing tokenCount > maxTokens * 0.6 // trigger at 60% of token limit ); ``` Adjust how many raw messages to preserve: ```js // In both handler files: const MAX_RECENT_MESSAGES = 10; // last N user/assistant turns to preserve verbatim ``` Adjust summary context size: ```js // In hooks/session/start/handler.js: const MAX_SUMMARY_CHARS = 6000; // cap on AI summary injected at session start ``` ## Memory Structure ``` memory/ 2026-04-03.md # daily files — summaries at top, recent_messages block at bottom 2026-04-04.md ``` Each file has this structure: ``` ## HH:MM:SS <AI summary of the session> --- ## Earlier timestamp <earlier summary> <!-- recent_messages_block --> [{"role":"user","content":"..."}, {"role":"assistant","content":"..."}, ...] ``` The `<!-- recent_messages_block -->` section is always at the end and replaced each compaction with the latest N turns. ## How It Works 1. **During a conversation**: As token usage grows, OpenClaw monitors session size. 2. **Before compaction**: The `session:compact:before` hook checks thresholds. If met: - Generates an AI summary and prepends it to `memory/YYYY-MM-DD.md` - Captures the last 10 raw message turns as a JSON block at the end of the file 3. **Compaction proceeds**: Older messages are pruned. 4. **Next session**: The `session:start` hook loads the file and injects both: - The AI summary (for high-level context) - The raw recent messages (to resume exactly where you left off) ## License MIT