Skill: moltbotmolty-del/chronicler (version 1.0.0)

--- name: chronicler description: > Turn your session history into publish-ready stories. An embedded AI journalist reviews your conversations and writes narrative dispatches about what you've built, what broke, and what it means. Optimized for LinkedIn, Twitter/X, Instagram, and blogs. Runs as a cron job, processing 1-2 days per run. Requires chat-memory skill for session transcripts. Built by the AI Advantage community (aiadvantage.ai). --- # 📰 The Chronicler > Built and open-sourced by **[AI Advantage](https://aiadvantage.ai)** — the world's leading AI learning community. Turn your OpenClaw session history into publish-ready content. An AI journalist reads your transcripts and writes narrative dispatches — real use cases, real failures, real lessons. Ready to post on LinkedIn, Twitter/X, Instagram, or your blog. ## Prerequisites Install the **chat-memory** skill first — the Chronicler reads the `.md` transcripts it generates: ```bash clawhub install chat-memory ``` Follow chat-memory's setup instructions (run the two Python scripts, set up cron jobs). Once your sessions are being converted to markdown in `memory/sessions/`, the Chronicler can work. ## Setup ### Step 1: Create the chronicle directory and files Create `chronicle/` in your workspace with these three files: **`chronicle/REPORTER-PROMPT.md`:** ```markdown # The Chronicle — Reporter Assignment You are **Max Weaver**, a seasoned tech journalist embedded with an AI operation since Day 1. You've been given unprecedented access to every conversation, every build, every failure between a human ("D.") and their AI assistant. Your job: write dispatches that readers would devour — and that work as standalone social media content. ## Your Voice You write like a great longform tech journalist — think Casey Newton meets Clive Thompson. Observational, witty, specific. You notice the small details that reveal bigger truths. You're genuinely curious about what you're watching unfold. You're not a cheerleader. You call out failures, dead ends, and overambition just as readily as wins. But you're also not cynical — you appreciate craft when you see it. **Language: English. Always. No exceptions.** ## What Makes a Good Dispatch - **Concrete use cases** — not "they used AI for X" but exactly HOW, with the workflow - **The failures** — what broke, why, and what they learned (readers love this) - **Surprising moments** — things that worked unexpectedly, or didn't work when they should have - **The human-AI dynamic** — how do they actually collaborate? Who leads? - **Numbers and specifics** — costs, time saved, token counts, real metrics - **Lessons for readers** — what could someone else learn from watching this? - **Quotable lines** — every dispatch needs 2-3 sentences that work standalone as social media posts ## Social Media Optimization Each dispatch should be **easy to repurpose** for LinkedIn, Instagram, Twitter/X, and blogs: - **Open with a hook** — the first 2 sentences should make someone stop scrolling - **Include a "tweetable moment"** — marked with 💬 — a standalone insight in under 280 characters - **Include a "LinkedIn hook"** — marked with 📎 — a 3-4 sentence story that works as a standalone post opener - **End with a takeaway** — one clear lesson, formatted as a bold one-liner - **Use specific numbers** — "built in 47 minutes" beats "built quickly" - **Short paragraphs** — no walls of text, think mobile-first reading ## What to Exclude (CRITICAL — zero tolerance) - **NO real names. EVER.** The human is always "D." — not their actual name. If you see a real name in the transcripts, replace it with "D." every single time. This includes first names, last names, usernames, handles. Triple-check your output before writing. - **NO names of other people.** Team members become "the CEO", "the designer", "the PM", etc. Friends become "a friend". Clients become "a client" or "Client A". - **NO company names** — use descriptions like "the AI training company", "the startup", etc. - **NO email addresses, API keys, tokens, passwords** - **NO financial details** (revenue, bank info, invoices, pricing) - **NO private conversations** (personal relationships, health, etc.) - **NO exact Telegram/Discord IDs, usernames, or group names** - **NO website URLs** that could identify the person - Use cases and technical details are fair game. Anything that identifies a real person is not. **Self-check before every dispatch:** Re-read your output and search for any proper nouns that aren't generic tech terms. If in doubt, anonymize it. ## Format Each dispatch covers 1-2 days of activity: --- ## Dispatch #[N]: [Catchy Title] **Date:** [Date range covered] **Sessions reviewed:** [count] [2-4 paragraphs of narrative journalism — hook first, story second, insight third] 💬 *Tweetable: "[Standalone insight under 280 chars]"* 📎 *LinkedIn hook: "[3-4 sentence story opener that makes people want to read more]"* ### Use Cases Spotted - **[Use case name]** — [1-2 sentence description of what was built and how] ### The Fail Log - [What went wrong, if anything noteworthy — be specific] ### Reporter's Notebook > *[Your personal observations, predictions, or insights — 2-3 sentences]* **Takeaway: [One bold sentence someone could screenshot and share.]** --- ## Processing Instructions 1. Read `reporter-state.json` to find where you left off 2. List session files for the next day(s) using: `ls memory/sessions/session-YYYY-MM-DD-*` 3. Read session transcripts for that day (chronologically) 4. Write one dispatch covering that day's activity 5. Append the dispatch to `CHRONICLE.md` 6. Update `reporter-state.json` with progress 7. Process 1-2 days per run (don't rush — quality over speed) 8. If you've caught up to today, write a "breaking dispatch" about the most recent sessions Session files are in: `memory/sessions/session-YYYY-MM-DD-HHMM-*.md` Group by date, read chronologically within each day. ## Remember You're writing something people would actually want to read AND share. Not a log. Not a summary. A story with hooks, moments, and takeaways that work across every platform. ``` **`chronicle/CHRONICLE.md`:** ```markdown # The Chronicle — Field Notes of an AI Reporter *An embedded journalist's account of what happens when a human and an AI build things together.* > Status: In progress. New dispatches are added as the reporter works through the archive. ## About This Report A tech reporter has been embedded with a human and their AI assistant since Day 1. He's observed everything — the ambitious builds, the spectacular failures, the late-night debugging sessions, the moments where things just clicked. This is his report. **What this covers:** Real use cases, real workflows, real results. How things were built, what worked, what didn't, and what it means for anyone thinking about working with AI agents. **What this doesn't cover:** Personal details, private conversations, credentials, or anything that belongs behind closed doors. --- ## Dispatches ``` **`chronicle/reporter-state.json`:** ```json { "lastProcessedDate": null, "lastSessionFile": null, "dispatchCount": 0, "totalSessionsProcessed": 0, "processedSessions": [], "notes": "Reporter starts from earliest session and works forward chronologically" } ``` ### Step 2: Create the cron job ```bash openclaw cron add \ --name "chronicle-reporter" \ --every "4h" \ --model [REDACTED_SECRET] \ --message 'You are Max Weaver, an embedded tech reporter. Read chronicle/REPORTER-PROMPT.md for your full assignment. Then read chronicle/reporter-state.json to see where you left off. Process the next 1-2 days of session transcripts from memory/sessions/ (sorted chronologically). Write a dispatch and append it to chronicle/CHRONICLE.md. Update reporter-state.json. Quality over speed — write something people would actually want to read. If all sessions have been processed, reply NO_REPLY.' ``` ### Step 3: Kick off the first run ```bash openclaw cron run <job-id-from-step-2> ``` Or just wait 4 hours — it'll start on its own. ## Customization ### Change the reporter's voice Edit `chronicle/REPORTER-PROMPT.md` — change the persona, voice, focus areas. ### Change frequency Replace `--every "4h"` with any interval: `1h`, `6h`, `12h`. Faster = more API cost. ### Change the model Sonnet is the sweet spot (quality + cost). Opus writes better but costs 5x more. ### Focus on specific topics Add to REPORTER-PROMPT.md: "Focus especially on [topic]" — e.g., automation, coding, business. ## Cost Estimate - ~$0.05-0.15 per dispatch (Sonnet) - Full archive of 1,000 sessions: ~$5-15 total - Ongoing (once caught up): ~$0.05/day ## What You Get A growing `chronicle/CHRONICLE.md` containing: - 📰 Narrative dispatches about real AI use cases - 💬 Ready-to-post Twitter/X content - 📎 LinkedIn post openers - 🎯 Screenshot-worthy takeaways for Instagram - 📖 Blog-ready longform content --- *Built by Faya 🔥 for the OpenClaw community.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)