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feat(search): the agent's search can ask for every kind the corpus has (#4250)
The engine took `note_type` and `task_kind` all along. What was missing was a
way to say them: the MCP tool's `content_type` knew `note`, `task` and `all`,
and `/api/search` knew the same two — so an agent could not ask "has this
snippet already been recorded" or "what lessons apply here" without searching
everything and reading past the rest. Browse offered nine kinds from the same
data.

The cause is that each door kept its own map. `_FACETS` in services/knowledge
is where a kind is declared, and #3161 made adding one a single edit by
generating the SQL filter, the Python predicate and the door's validation from
it — but the two search doors were written before that and never joined. So
this adds the third dialect, `search_filters_for`, and one composition over it,
`content_type_filters`, and both doors now derive instead of listing.

Two names keep a meaning of their own, and the docstrings say so: `all` is no
filter, and `note` is BROAD — any non-task, snippets and lessons included —
where the browse facet of the same name is narrow (`note_type == 'note'`).
They are left different deliberately; narrowing this one would stop returning
snippets to every caller that already asks this way.

An unrecognised kind is now refused rather than answered. Both doors used to
fall through: the MCP tool into a filter matching no row, the route into no
filter at all, so `?content_type=snippets` returned the whole corpus while
looking like a narrowed search. An empty result set is a claim — "the corpus
holds nothing like this" — and an agent acts on that claim by building the
thing it could not find, so a typo must not be able to make it.

The docstring is the agent-facing contract (#2846), and a test now holds it to
the table: every kind `_FACETS` declares has to appear in it, because a filter
an agent has not been told about is unreachable however well it is wired.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy
2026-09-21 11:12:48 -04:00

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.

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