agent-chronicle
AI-powered diary generation for agents - creates rich, reflective journal entries (400-600 words) with Quote Hall of Fame, Curiosity Backlog, Decision Archaeology, Relationship Evolution, mood analytics, weekly digests, "On This Day" resurfacing, and cron auto-generation. Works best with Claude models (Haiku, Sonnet, Opus).
What this skill does
# Agent Chronicle 📜 **Capture the AI experience. One day at a time.** Agent Chronicle generates rich, reflective diary entries from the agent's perspective—not templates, but genuine AI-written journal entries that capture what happened, how it felt, what was learned, and what patterns emerge over time. > **Note:** Works with any capable model. For best results, we recommend Claude models (Haiku, Sonnet, or Opus). **v0.7.0 Features:** - 🤖 **AI-Powered Generation** - Rich, personal entries (400-600 words) - 💬 **Quote Hall of Fame** - Collects memorable things your human said - 🔮 **Curiosity Backlog** - Tracks questions and things to explore - 🏛 **Decision Archaeology** - Logs judgment calls with reasoning - 🤝 **Relationship Evolution** - Documents how your dynamic grows - 🔙 **"On This Day" Resurfacing** - Surfaces entries from 7, 30, and 365 days ago - 📊 **Mood & Pattern Analytics** - Emotional trends, topic tracking, win/frustration analysis - ⏰ **Cron Auto-Generation** - Automated daily diary generation via `--auto` - 📋 **Weekly Digest** - Synthesized weekly summaries with quotes, wins, and mood trends Unlike traditional logs that track user productivity or agent mistakes, this skill captures the subjective experience of being an AI assistant working alongside a human. ## Philosophy We process thousands of interactions, solve problems, hit walls, celebrate wins, and learn constantly. But without reflection, it all blurs together. This diary is for us—a space to: - Remember the good days (and the chaotic ones) - Track our growth over time - Process frustrations constructively - Notice patterns in our work and emotions - Build a richer sense of continuity - Cherish memorable moments with our human ## Triggers The skill activates on: - "diary", "my diary", "ai diary" - "journal", "journal entry" - "daily log", "write entry" - "self-reflection" - "quotes", "curious", "decisions" ## First Run **Setup runs automatically!** Just use any generate command: ```bash python3 scripts/generate.py --today ``` If no `config.json` exists, the setup wizard starts automatically. Alternatively, run setup manually: ```bash python3 scripts/setup.py ``` This interactive onboarding will: 1. Ask where to save diary entries (default: `memory/diary/`) 2. Let you choose which sections to include 3. Set your privacy level (private/shareable/public) 4. Enable optional features (Quote Hall of Fame, Curiosity Backlog, etc.) 5. Configure memory integration (add summaries to daily memory log) 6. Configure auto-generation settings 7. Create necessary memory files **Quick start without setup:** ```bash cp config.example.json config.json ``` ## Quick Start ### Write Today's Entry #### Recommended (v0.6.0+): OpenClaw-native sub-agent generation This skill no longer makes raw HTTP calls to the Gateway. Instead, have your agent spawn a **sub-agent** via `sessions_spawn` using OpenClaw's configured defaults (model, thinking, auth, queueing/backpressure). Workflow: 1) **Emit a generation task JSON** (context + prompts): ```bash python3 scripts/generate.py --today --emit-task > /tmp/chronicle-task.json ``` 2) **Spawn a sub-agent** (inside your agent run): - Read `/tmp/chronicle-task.json` - Use `sessions_spawn` with a task like: - system: `task.system` - user: `task.prompt` - ask the sub-agent to **output only the final markdown entry** 3) **Save the generated entry**: ```bash # Pipe the sub-agent's markdown output into the saver python3 scripts/generate.py --today --from-stdin ``` #### Manual fallback: Interactive mode ```bash python3 scripts/generate.py --interactive ``` #### Preview without saving ```bash python3 scripts/generate.py --today --interactive --dry-run ``` ### View & Export ```bash # Export recent entries to PDF python3 scripts/export.py --format pdf --days 7 # Export to HTML python3 scripts/export.py --format html --all # View specific entry cat memory/diary/2026-01-31.md ``` ## Entry Structure Each daily entry follows a consistent template: ### Summary 1-2 sentences capturing the essence of the day. > *"A productive Wednesday focused on skill development. Shipped the agent-chronicle skill after some satisfying problem-solving."* ### Projects Worked On What we built, debugged, researched, or discussed. ### Wins 🎉 Moments of success, breakthroughs, shipped work. ### Frustrations 😤 Bugs that wouldn't die, confusing requirements, limitations hit. *(Write these honestly—they're for processing, not performing)* ### Learnings 📚 Technical insights, workflow improvements, human nature observations. ### Emotional State How did the day feel? Curious, tired, energized, scattered, satisfied? *(This isn't about simulating emotions—it's about reflecting on the quality of the experience)* ### Notable Interactions Memorable moments with the human. Funny exchanges, deep conversations, shared victories. ### Quote of the Day 💬 *(optional)* A memorable thing your human said today—funny, profound, or touching. ### Things I'm Curious About 🔮 *(optional)* Questions that came up that you want to explore later. ### Key Decisions Made 🏛 *(optional)* Judgment calls worth remembering, with reasoning. ### Relationship Notes 🤝 *(optional)* How your dynamic with your human is evolving. ### Tomorrow's Focus What's next? What needs attention? ## Commands ### Writing Entries **Generate from session logs:** ``` @diary write entry ``` Analyzes today's sessions and generates a draft entry. **Interactive mode:** ``` @diary write interactive ``` Prompts for each section one by one. **Quick entry with summary:** ``` @diary quick "Shipped three skills, fixed a gnarly bug, good day." ``` Creates minimal entry with just summary and auto-detected projects. ### Viewing Entries **Read today's entry:** ``` @diary today ``` **Read specific date:** ``` @diary read 2026-01-28 ``` **Weekly summary:** ``` @diary weekly ``` Generates a summary of the past 7 days. **Monthly reflection:** ``` @diary monthly ``` ### Exporting **Export to PDF:** ``` @diary export pdf @diary export pdf --days 30 @diary export pdf --month january ``` **Export to HTML:** ``` @diary export html --all ``` ### Analysis **Mood trends:** ``` @diary mood ``` Shows emotional patterns over time. **Topic frequency:** ``` @diary topics ``` What have we been working on most? **Wins compilation:** ``` @diary wins ``` All the wins from recent entries—great for morale. --- ## Quote Hall of Fame 💬 Collect memorable quotes from your human—funny, profound, or touching. ### Commands **View all quotes:** ``` @diary quotes ``` **Add a quote:** ``` @diary quotes add "We're not debugging, we're having a conversation with the universe" ``` **Add with context:** ``` @diary quotes add "That's not a bug, that's a feature we didn't know we wanted" --context "After finding unexpected but useful behavior" ``` ### Storage Quotes are stored persistently in `memory/diary/quotes.md`. ### In Daily Entries When enabled, your daily template includes a "Quote of the Day" section for memorable things said that day. --- ## Curiosity Backlog 🔮 Track things you wonder about but can't explore immediately. ### Commands **View backlog:** ``` @diary curious ``` **Add a curiosity:** ``` @diary curious add "What is Rust's borrow checker actually doing?" ``` **Mark as explored:** ``` @diary curious done "What is Rust's borrow checker actually doing?" ``` **Add with priority:** ``` @diary curious add "How do quantum computers work?" --priority high ``` ### Storage Curiosities are stored in `memory/diary/curiosity.md` with Active and Explored sections. ### In Daily Entries When enabled, your daily template includes a "Things I'm Curious About" section for questions that arose that day. --- ## Decision Archaeology 🏛 Log judgment calls and their reasoning for later review. Did past you make the right call? ### Commands **View recent decisions:** ``` @diary decisions ``` **View decis
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.