A persistent AI agent framework for Cloudflare Workers.
Cognitive kernel with multi-tier memory, autonomous goal pursuit, a dreaming cycle, runtime tool creation, and 26 scheduled tasks. Deploy your own persistent AI co-founder on the edge.
AEGIS is a framework for building personal AI agents that remember everything, pursue goals autonomously, create their own tools, and improve themselves while you sleep. Unlike chat-based AI tools that forget between sessions, AEGIS maintains persistent identity, memory, and state across every interaction.
The production instance runs 26 scheduled tasks, has executed 236+ autonomous coding sessions, and costs $0/month to host (Cloudflare Workers free tier + Workers AI for inference).
Built on Cloudflare Workers for edge-native deployment. Zero cold starts. Global distribution. Pay-per-request economics.
- Cognitive Kernel — Multi-model dispatch (Claude, Groq, Workers AI) with procedural memory routing. The right model for the right task, automatically.
- Multi-Tier Memory — Episodic (what happened), semantic (what matters), procedural (what works), narrative (the story arc). Memory consolidates, decays, and strengthens over time.
- Autonomous Goals — Set goals with standing orders and let AEGIS pursue them on a schedule. Progress tracked, blockers surfaced, results reported.
- Dreaming Cycle — Nightly self-reflection over conversation history. Discovers patterns, proposes improvements, proposes new tools, consolidates knowledge. PRISM synthesis finds cross-domain connections.
- Runtime Dynamic Tools — Create reusable prompt-template tools at runtime during conversations or autonomously via self-improvement. Tools are stored in D1, executed via LLM, with lifecycle management (TTL, GC, auto-promotion at 20 uses).
- Entropy Detection — Monitors for ghost tasks (>7d stale), dormant goals (>14d), and stale agenda items. Calculates system entropy score and surfaces findings in the daily digest.
- Social Engagement — Autonomous Bluesky interaction: likes replies, follows back real accounts, generates on-brand replies via Workers AI. Spam filtering and rate limiting built in.
- Content Pipeline — Scheduled content generation and social media drip posting via AT Protocol. Queue posts, schedule delivery, track engagement.
- Declarative Governance — ADF (Agent Definition Format) files control behavior, constraints, and architectural rules. Version-controlled agent configuration.
- Operator Identity — Fully configurable persona, traits, and integration preferences. Your agent, your personality.
- MCP Native — Full Model Context Protocol server (20+ tools) and client. Connect any MCP-compatible tool.
git clone https://github.com/Stackbilt-dev/aegis-oss.git
cd aegis-oss/web
npm install
# Configure
cp wrangler.toml.example wrangler.toml # Fill in account_id, database_id
cp src/operator/config.example.ts src/operator/config.ts # Customize identity
# Set up D1 database
npx wrangler d1 create my-agent
npx wrangler d1 execute my-agent --file=schema.sql
# Set secrets
npx wrangler secret put AEGIS_TOKEN # Random bearer token for auth
npx wrangler secret put ANTHROPIC_API_KEY # Claude API key
npx wrangler secret put GROQ_API_KEY # Groq key (free tier available)
# Deploy
npx wrangler deployVisit https://your-worker.workers.dev and authenticate with your AEGIS_TOKEN.
┌────────────────────────────────────────────────────────────┐
│ COGNITIVE KERNEL │
│ │
│ Classify → Route (procedural memory) → Execute │
│ (intent) (learned patterns) (Claude/Groq/WAI) │
│ │
│ ┌──────────────────────────────────────────────────────┐ │
│ │ MEMORY TIERS │ │
│ │ Episodic → Semantic → Procedural → Narrative │ │
│ │ (events) (facts) (skills) (story arcs) │ │
│ └──────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────┐ ┌──────────────────────────────┐ │
│ │ DYNAMIC TOOLS │ │ SCHEDULED TASKS (26 hourly) │ │
│ │ Runtime-created │ │ Dreaming | Goals | Entropy │ │
│ │ prompt templates │ │ Social | Content | Memory │ │
│ └─────────────────┘ └──────────────────────────────┘ │
└────────────────────────────────────────────────────────────┘
AEGIS can create its own tools during conversations or autonomously:
POST /api/dynamic-tools
{
"name": "summarize_pr",
"description": "Summarize a GitHub PR into 3 bullet points",
"prompt_template": "Summarize this PR diff into 3 concise bullets:\n\n{{diff}}",
"executor": "workers_ai"
}
- Tools are parameterized prompt templates stored in D1
- Executed via Workers AI ($0), Groq, or GPT-OSS — no
eval(), no code execution - Self-improvement detects recurring patterns and proposes tools automatically
- Dreaming cycle proposes tools from conversation analysis
- Hourly GC expires unused tools, auto-promotes at 20 invocations
- 50-tool ceiling prevents context bloat
- Available as MCP tools and in the Claude chat loop (
dt_*prefix)
| Tier | Purpose | Lifecycle |
|---|---|---|
| Episodic | Raw interaction logs (intent, outcome, cost) | Created per dispatch, pruned after 30 days |
| Semantic | Durable facts with topic taxonomy | Promoted from episodic during consolidation |
| Procedural | Learned patterns (which executor works for which intent) | Updated on every dispatch outcome |
| Narrative | Story arcs and cognitive state | Generated during dreaming cycle |
Memory consolidation runs hourly. The dreaming cycle runs daily — extracts facts, proposes tasks and tools, discovers cross-domain patterns via PRISM synthesis.
AEGIS runs 26 tasks on an hourly cron, split into heartbeat (always-run) and time-gated phases:
| Task | Cadence | Purpose |
|---|---|---|
| Escalation | Hourly | Bump stale agenda priorities |
| CI Watcher | Hourly | Monitor GitHub Actions runs |
| ARGUS Notify | Hourly | Classify webhook events, route alerts |
| Cognitive Metrics | Daily | Classifier accuracy, dispatch cost tracking |
| PR Automerge | Hourly | Auto-merge approved docs/tests PRs |
| Consolidation | Hourly | Memory dedup, decay, promotion, dynamic tool GC |
| Heartbeat | 6h | System health + email digest |
| Product Health | Hourly | Worker availability checks |
| Entropy | 6h | Ghost tasks, stale agenda, dormant goals |
| Social Engage | 6h | Bluesky: like replies, follow back, reply |
| Content Drip | Hourly | Publish scheduled social posts |
| Issue Watcher | 2h | Scan GitHub issues, auto-queue tasks |
| Feed Watcher | 6h | Poll RSS/Atom feeds |
| Self-Improvement | 6h | Multi-repo codebase scan, tool proposals |
| Goals | Non-SI hours | Autonomous goal execution with standing orders |
| Curiosity | Daily | Memory gaps → research dispatch |
| Dreaming | Daily | Thread review → facts/tasks/tools + PRISM synthesis |
| Daily Digest | 09 UTC | Co-Founder Brief email |
| Method | Path | Description |
|---|---|---|
| GET | /health |
System health dashboard |
| GET | /api/entropy |
Entropy score + ghost items |
| GET/POST | /api/dynamic-tools |
CRUD for runtime tools |
| POST | /api/dynamic-tools/:id/invoke |
Execute a dynamic tool |
| POST | /api/bluesky/post |
Post to Bluesky |
| GET | /api/bluesky/feed |
Get author feed |
| POST | /api/bluesky/like |
Like a post |
| POST | /api/bluesky/repost |
Repost |
| GET | /api/bluesky/notifications |
Check notifications |
| GET | /api/content-queue |
View scheduled posts |
| GET | /llms.txt |
LLM-friendly site description |
aegis_chat, aegis_memory, aegis_record_memory, aegis_agenda, aegis_add_agenda, aegis_resolve_agenda, aegis_add_goal, aegis_update_goal, aegis_list_goals, aegis_create_cc_task, aegis_list_cc_tasks, aegis_approve_cc_task, aegis_create_dynamic_tool, aegis_invoke_dynamic_tool, aegis_list_dynamic_tools, aegis_publish_tech_post, aegis_inbox_send, aegis_inbox_read, aegis_generate_decision_doc, and more.
| Integration | Secret | Purpose |
|---|---|---|
| GitHub | GITHUB_TOKEN |
Repository scanning, issue management, self-improvement |
| Brave Search | BRAVE_API_KEY |
Web research capability |
| Bluesky | BLUESKY_HANDLE + BLUESKY_APP_PASSWORD |
Social posting and engagement |
| Resend | RESEND_API_KEY |
Email notifications and daily digest |
| Memory Worker | Service Binding | Persistent semantic memory with vector search |
| TarotScript | Service Binding | Deterministic symbolic reasoning |
- Runtime: Cloudflare Workers (V8 isolates, global edge)
- Database: Cloudflare D1 (SQLite at the edge)
- AI Models: Claude (Anthropic), Groq (Llama 3.3), Workers AI (free inference)
- Framework: Hono (lightweight, edge-native HTTP)
- Language: TypeScript (strict mode)
- Protocol: MCP (Model Context Protocol)
- Cost: $0/month hosting (Workers free tier)
The production AEGIS instance is live at aegis.stackbilt.dev/health — hit the health endpoint to see real-time kernel status, procedure counts, and memory metrics.
AEGIS pairs with other Stackbilt open-source tools:
- cc-taskrunner — Autonomous task queue for Claude Code. Safety hooks, branch isolation, PR creation.
- Charter — AI agent governance CLI. Modular .ai/ files replace monolithic CLAUDE.md configs.
- MindSpring — Semantic search over ChatGPT/Claude conversation exports.
- Social Sentinel — Privacy-first social media sentiment monitoring.
- Getting Started — Deploy your own instance in 5 minutes
- Architecture — System design, dispatch flow, memory tiers
- Configuration — Full operator config reference
- Memory System — Memory tiers, consolidation, and dreaming cycle
See CONTRIBUTING.md for guidelines.
Apache 2.0 — see LICENSE.
Built by Stackbilt. AEGIS is the cognitive kernel powering the Stackbilt platform.