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feat(telemetry): tell a ranker decline from a repeat before the observation window opens (#3497)
Making the rule arms log every call exposed a second ambiguity in the same
row. `result_count == 0` is two unrelated events wearing one number:

  - the ranker found nothing above the bar — the only evidence a threshold is
    set too high; and
  - the ranker found only what this session had already been shown — which
    says nothing whatever about the bar.

A long session excludes its way into the second, so the arm reads worse the
longer it runs correctly. Rows written now carry the ambiguity permanently,
which is why this lands before any watch period rather than after.

`retrieval_logs.suppressed_count` (0095, nullable) holds what the caller
dropped as already-shown. Both rule arms report it; they filter in Python and
always know. The note arms pass exclusions INTO semantic_search_notes and
never see what was dropped, so they store NULL.

THE NULL IS LOAD-BEARING. It means "not measured here", and the readout
renders it as `suppression: null` rather than a zeroed dict. Defaulting to 0
would let an unmeasured surface read as a perfectly clean one — the same
substitution of an artifact for a measurement that #3311 made. No backfill,
for the same reason: existing rows genuinely do not know.

`retrieval_telemetry`'s `sources` gains `suppression` with `measured_calls`,
`calls_with_suppression` and `zero_because_already_shown`; subtract the last
from `zero_result_calls` for the true ranker declines. The MCP tool docstring
says to read the two together and warns against reading the null as a zero.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011cPyzNnegXHr5iRMzzy5KJ
2026-09-03 21:12:38 -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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