Always-on rules were on-demand, not always-present: Tier-1 static context only
tells the agent to call list_always_on_rules(), and Tier-2 dynamic fetch is dark
(token doesn't reach the hook subprocess). On compaction the fetched rules get
summarized away while the harness's own built-in git instruction ("branch first")
survives in the base prompt — so post-compact the generic git instinct wins and
rule #1 ("dev is home") is missed.
- scribe_static_context.md: new "Operator rules govern consequential actions"
bullet — before any git branch/commit/push or hard-to-reverse action, loaded
rules beat generic harness/default habits; re-pull rules if not loaded or
summarized by a compaction. Tier 1 = always fires, keyless, re-fires on compact.
- scribe_session_context.sh: compaction banner now re-pulls list_always_on_rules(),
not just enter_project().
- plugin.json: 0.1.10 → 0.1.11 so autoUpdate ships the plugin/ change (#1040).
Generic and instance-agnostic per rules #115/#119 — no operator-specific rule
text hardcoded. Refs issue #1197.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01E4bNefPFAz7esmMZMZmkzL
Fabled Scribe
A self-hosted second brain and project management application with integrated LLM capabilities. Write, organise, and act on your notes and tasks with the help of a local AI assistant — all running on your own hardware.
Features
Notes and tasks with a Markdown editor, sub-tasks, milestones, and kanban project workspaces. AI chat with streaming responses, RAG over your notes, and tool use (web search, calendar, weather). A daily briefing that digests your tasks, RSS feeds, and weather on a schedule. Knowledge graph, per-user/group sharing, PWA with push notifications, and an MCP server for external AI clients.
Quick Start
Prerequisites: Docker and Docker Compose. 8 GB+ RAM recommended for LLM inference.
Download docker-compose.quickstart.yml from this repo, then:
# Optional but recommended — set a secret key
export SECRET_KEY=your-random-secret-here
docker compose -f docker-compose.quickstart.yml up -d
Open http://localhost:5000. The first user to register becomes admin. Go to Settings → General to pull an LLM model — qwen3:8b or llama3.1:8b are good starting points.
GPU: Ollama runs CPU-only by default. See the comments in
docker-compose.quickstart.ymlto enable NVIDIA GPU passthrough.
Development: To build from source, see Development.
Documentation
| Doc | Contents |
|---|---|
| Architecture | Stack, design decisions, data models, key services |
| Configuration | Environment variables, Docker Compose, production setup, security |
| Features | Detailed feature breakdown and keyboard shortcuts |
| Development | Dev workflow, CI/CD, migrations, release process |
| API Keys & MCP | API key management and Fable MCP install guide |
| SSO / OAuth | OIDC setup for Authentik, Keycloak, and other providers |
| API Reference | All REST API endpoints |
License
This project is privately maintained.