bvandeusen
0d4b155699
The readout already grouped usage by source — `group_by(event, source)` — and the loop directly below it threw the source away, collapsing every surface into one corpus-wide ratio. So the question a threshold is actually tuned against, "is THIS surface worth its noise", could not be asked of any surface, while the data to answer it sat in the table. `usage.by_source` reports notes_surfaced / notes_pulled / pull_through per surface. The grain is the note, not the call: a pull records the door it came through, not the surface that led there, so grouping the pulled rows by source would answer a different question. Joining surfaced rows to pulled rows on note_id answers this one without the session identity #2085 declined to invent — at the cost of being an upper bound per surface, which the docstring says where it is read. Ambient surfaces report counts and a null ratio: nothing chose those records, so "surfaced often, opened never" is not a judgment about them. A surface that genuinely produced nothing reports 0.0, which must not look like the null. The join is guarded separately from the two reads above it. #2663 was a novel SQL shape the database rejected inside a broad except; this is the novel shape here, and it must not take down two readouts that work. Tests are integration for that same reason — a mock passes on a query Postgres refuses. They pin the distinct-first property (three surfacings of one note are one note), the ambient null, and the LIKE escape, since an unescaped `mcp_%` also matches `mcpXget_note` and nothing else in the payload would show the difference.
Fabled Scribe
A self-hosted work system-of-record for software projects, built to be driven by Claude Code. Notes, tasks, issues, projects, milestones, rules, and stored processes — reachable from Claude via a built-in MCP endpoint and a bundled Claude Code plugin, with a clean web UI for humans. No in-app LLM; Claude is the sole assistant.
Features
Notes and tasks with a Markdown editor, sub-tasks, milestones, issues, and kanban project workspaces. Stored processes, an engineering rulebook system (with an inception step that decides what each project inherits), and semantic search with proactive knowledge-injection into Claude's context. A knowledge graph, per-user/group sharing, and a built-in MCP server (/mcp) plus a bundled Claude Code plugin so Claude can record and recall your work directly.
Quick Start
Prerequisites: Docker and Docker Compose. No GPU or local model needed — Claude is the sole assistant, reached over MCP.
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. To connect Claude, create an API key under Settings → API Keys and install the Claude Code plugin — see API Keys & MCP.
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.