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Workflows

Learn effective patterns for using Flowbaby in your daily development.

Usage​

Flowbaby can automatically search your workspace memory and surface relevant context into GitHub Copilot chats.

How it works:

  • Flowbaby watches for conversation cues (e.g., "How did I implement…?", "What did we decide about…?").
  • When it detects a good opportunity, it runs a background search against your knowledge graph.
  • Retrieved memories are added to the Copilot request as additional context so you don't have to restate prior work.

What you'll see:

  • In Copilot Chat, Flowbaby shows a section like "📚 Retrieved memories" with short previews.
  • Copilot's answer incorporates those memories directly into its response.

2. Context-Aware Automatic Memory Storage​

Flowbaby can also decide when to summarize and store parts of the conversation as long-term memory.

How it works:

  • Flowbaby looks for moments where you've reached a decision, finished a debugging session, or explained an important concept.
  • It generates a structured summary and stores it in your workspace knowledge graph (after any required confirmation, depending on settings).

Benefits:

  • You build up high-value memory over time with minimal manual effort.
  • Later queries can retrieve these summaries instead of raw, noisy chat logs.

3. Using the @flowbaby Chat Participant​

The @flowbaby participant lets you directly query your workspace memory.

How to use:

  1. Open GitHub Copilot Chat (Ctrl+Alt+I or click the chat icon).
  2. Address Flowbaby explicitly: @flowbaby How did I implement caching?
  3. Flowbaby:
    • Retrieves relevant memories from your knowledge graph.
    • Shows previews under "📚 Retrieved memories".
    • Augments your question with that context.
    • Generates a context-aware response.

Example queries:

  • @flowbaby What problems did we discuss about the authentication system?
  • @flowbaby What solutions did we consider for rate limiting?
  • @flowbaby Summarize our decisions about database architecture

4. Keyboard Shortcut and Command Palette Capture​

Use these flows when you want to explicitly capture important information.

Keyboard shortcut:

  1. View a valuable chat message (from any participant: @workspace, @terminal, GitHub Copilot, etc.).
  2. Press Ctrl+Alt+F (or Cmd+Alt+F on macOS).
  3. Paste or confirm the content in the capture input.
  4. Press Enter to capture.
  5. You'll see a staged message (e.g., "Memory staged - processing will finish in ~1–2 minutes").

Command Palette:

  1. Open Command Palette (Ctrl+Shift+P / Cmd+Shift+P).
  2. Run "Flowbaby: Capture to Memory".
  3. Follow the same flow as the keyboard shortcut.

5. Background Async Ingestion​

Flowbaby processes captured memories asynchronously so your editor stays responsive.

Timeline:

  • Capture confirmation: ~5–10 seconds.
  • Background processing and graph construction: ~60–90 seconds.
  • Total time from capture to searchable memory: ~1–2 minutes.

You'll receive a notification when ingestion finishes (success or failure), including a brief digest and basic metrics in the logs.

6. Viewing Background Operations​

To inspect everything Flowbaby is doing in the background:

  1. Open Command Palette.
  2. Run "Flowbaby: View Background Operations".
  3. Review pending, running, completed, and failed ingestion tasks.

7. How Flowbaby Stores Summaries​

In normal use, Flowbaby creates and maintains summaries for you automatically.

Automatic summary creation:

  • When you reach an important conclusion, finish a debugging session, or make a design decision, Flowbaby may create a structured summary in the background.
  • These summaries capture topic, key decisions, rationale, open questions, and next steps.
  • They are stored in your workspace knowledge graph and later used by automatic search and the @flowbaby participant.

Manual and agent-driven summaries (optional):

  • You can still ask Flowbaby to create a summary explicitly if you want tighter control.
  • In Copilot Chat, you can say things like:
    • @flowbaby summarize this conversation
    • @flowbaby remember this session
    • @flowbaby create summary for this plan
  • Custom agents can also store summaries directly using Flowbaby's tools and APIs (see the Flowbaby docs at docs.flowbaby.ai).

The key idea: you don't need to manage summaries manually unless you want to - Flowbaby's automatic storage is usually enough.

8. How Flowbaby Retrieves Summaries​

Flowbaby uses summaries as a primary source of truth when answering questions about past work.

Automatic retrieval:

  • When context-aware search (Section 1) or the @flowbaby participant runs a query, Flowbaby searches both raw captured conversations and structured summaries.
  • When a good match is found, you'll see a "📚 Retrieved memories" section with previews of the most relevant items.

What summaries look like:

  • Organized sections: topic, key decisions, open questions, next steps, rationale.
  • Rich, human-readable text designed to be useful both to you and to the LLM.

How to prompt for past work:

  • @flowbaby What did we decide about Plan 013?
  • @flowbaby What questions are still open about memory transparency?
  • @flowbaby What are the next steps for the authentication system?
  • @flowbaby Show me the rationale for using enriched text format

You don't need a separate "retrieve summary" command-just ask @flowbaby questions about previous sessions or decisions, and Flowbaby will use summaries automatically when available.

9. Memory Management Commands​

Toggle Memory On/Off:

  • Command Palette → "Flowbaby: Toggle Memory"
  • Flips Flowbaby.enabled setting

Clear Workspace Memory:

  • Command Palette → "Flowbaby: Clear Workspace Memory"
  • Deletes all captured conversations for current workspace (requires confirmation)