Slack / Notion / Jira
        │
        ▼
┌───────────────────────────────────────────────────────────────────┐
│  STAGE A  Full Pull + Triage                                      │
│  Pulls everything since last sync — no keyword filtering.        │
│  Hard filter removes bots, duplicates, short messages.           │
└──────────────────────────┬────────────────────────────────────────┘
                           │
                           ▼
┌───────────────────────────────────────────────────────────────────┐
│  STAGE B  Batch LLM Signal Detection                              │
│  1 LLM call per 25 messages. Detects: decisions, policies,       │
│  architecture choices, metrics, risks.                           │
└──────────────────────────┬────────────────────────────────────────┘
                           │
                           ▼
┌───────────────────────────────────────────────────────────────────┐
│  STAGE C  Wiki Reconciliation                                     │
│  Maps each signal against your existing wiki. Classifies as:     │
│  NEW · UPDATE · SUPPLEMENT · CONTRADICT                          │
└──────────────────────────┬────────────────────────────────────────┘
                           │
                           ▼
┌───────────────────────────────────────────────────────────────────┐
│  STAGE D  Compile to Staging Branch                               │
│  Writes structured OKF Markdown files to a git staging branch.  │
│  Assigns review lanes: AUTO · QUICK · ATTN                       │
└──────────────────────────┬────────────────────────────────────────┘
                           │
                           ▼
┌───────────────────────────────────────────────────────────────────┐
│  STAGE E  Human Review Digest  (Streamlit UI)                    │
│  Reviewer approves proposals in under 10 minutes.                │
│  Approved content merges to main with a git commit hash.         │
└──────────────────────────┬────────────────────────────────────────┘
                           │
                           ▼
         MCP Server — serves wiki to Claude Code, Cursor, Windsurf

knowledgekeeper/
├── cli.py                  # Guided setup wizard + start/status commands
├── config.py               # Config dataclass, load/save YAML
├── connectors/
│   ├── base.py             # RawItem dataclass + ConnectorBase ABC
│   ├── slack_connector.py  # Full channel history pull
│   ├── notion_connector.py # Database page pull
│   └── triage.py           # Dedup + length + bot filter
├── pipeline/
│   ├── detector.py         # Stage B: batch LLM signal detection
│   ├── reconciler.py       # Stage C: wiki reconciliation (Pydantic AI)
│   ├── aggregator.py       # Merge proposals for same concept
│   ├── compiler.py         # Stage D: write to staging branch
│   └── runner.py           # Orchestrate A → B → C → D
├── okf/
│   ├── schema.py           # OKFConcept dataclass + frontmatter parse/render
│   ├── index_builder.py    # Rebuild index.md files
│   └── log_writer.py       # Append to audit log
├── git_ops/
│   └── manager.py          # Staging branch, merge, revert, read
├── digest/
│   └── ui.py               # Streamlit review UI (Proposals · Status · Settings)
├── mcp/
│   └── server.py           # FastMCP: get_knowledge_map, read_concept, get_changes
├── db/
│   └── store.py            # SQLite: sync state + run history
└── scheduler.py            # Nightly 22:00 pipeline + 08:00 notify

# 1. Install
git clone https://github.com/YOUR_USERNAME/knowledgekeeper
cd knowledgekeeper
python3 -m venv venv && source venv/bin/activate
pip install -e .

# 2. Pull the local LLM (or skip and use Anthropic)
ollama pull qwen3:4b

# 3. Guided setup — connects Slack + Notion, initialises wiki repo
knowledgekeeper init

# 4. Open the review digest
python3 -m streamlit run knowledgekeeper/digest/ui.py --server.port 8080

# 5. Start the nightly scheduler
knowledgekeeper start

python3 demo/run_pipeline.py

python3 scripts/run_test.py

{
  "mcpServers": {
    "knowledgekeeper": {
      "command": "python3",
      "args": ["-m", "knowledgekeeper.mcp.server"]
    }
  }
}

---
type: concept.decision
title: Supabase as Primary Database
domain: architecture
confidence: high
proposal_type: NEW
source_refs:
  - author: alex.chen
    channel: engineering
    platform: slack
approved_by: Sarah Okafor
git_commit: a1b2c3d
---

## Decision

The team selected Supabase as the primary database after evaluating
Supabase, Firebase, and PlanetScale...

~/my-wiki/
├── index.md          ← knowledge map (what MCP reads first)
├── log.md            ← full audit trail with commit hashes
└── okf/
    ├── architecture/ ← index.md + concept files
    ├── product/
    └── operations/

pytest tests/ -v
# 58 passed in 3.2s

tests/
├── test_config.py           test_git_manager.py
├── test_store.py            test_index_builder.py
├── test_slack_connector.py  test_index_scanner.py
├── test_notion_connector.py test_okf_schema.py
├── test_triage.py           test_okf_writer.py
├── test_detector.py         test_compiler.py
├── test_reconciler.py       test_runner.py
├── test_aggregator.py       test_scheduler.py
├── test_digest_ui.py        test_mcp_server.py