A WonderForge project.
CapstanAI - LabNote is a human-in-the-loop notebook for coordinating AI sessions through labelled packets, provenance-rich handoffs, JSON registry records, and traceable decisions.
It is designed for people who work across multiple AI sessions, assistants, models, or coding helpers, but do not want to pretend those systems share a single memory, identity, or brain.
No ghosts. No agents. No shared-memory theatre. No Skynet... we hope.
Just a well-labelled bridge.
CapstanAI - LabNote gives you a simple file-based workflow for:
- passing tasks between AI sessions
- recording who said what
- tracking packets, responses, and decisions
- keeping outputs reviewable
- preserving provenance
- avoiding giant paste-dumps and context confusion
- making AI assistants identifiable contributors instead of mysterious blobs of helpful fog
It is deliberately boring in the places where boring is useful.
CapstanAI - LabNote is not:
- an autonomous agent framework
- a background runner
- a shared-memory system
- a replacement for human judgement
- a secret automation layer
- a place to store credentials, private keys, tokens, or sensitive raw dumps
The human remains the decision-maker.
AI assistants may contribute, review, critique, and respond. The operator steers the ship.
CapstanAI - LabNote is a public template/reference repo.
This public repo is a template/reference scaffold. Do not store private runtime deposits, transcripts, credentials, private visitor records, or project-specific corpora here.
For live use, create or use your own private or controlled LabNote workspace.
In a controlled live workspace, routine deposits may write directly to the default branch.
Branches/PRs are reserved for procedure, policy, code, structure, cleanup, risky/bulky imports, many existing-file edits, or explicit review.
Canonical registry records are JSON-per-record under registry/.
CSV registries, if present, are legacy/optional rollups.
The basic pattern is:
Human or AI creates a packet
↓
Packet goes into the right inbox
↓
A receiving AI session reads only what it needs
↓
The receiving session writes a response
↓
The response is reviewed
↓
The decision is recorded
Each handoff should leave a clear trail:
packet → response → review → decision
AI sessions are useful, but they often suffer from:
- lost context
- repeated explanations
- unclear authorship
- messy handoffs
- overlong chats
- vague “we discussed this somewhere” memory sludge
CapstanAI - LabNote gives those sessions a shared external notebook without pretending they have shared internal memory.
It helps each assistant know:
Who am I in this workflow?
What has been handed to me?
Who is waiting for my answer?
What should I tell the operator?
What decision has already been made?
- Start at
AI_ENTRYPOINT.md. - Read
lobby/README_FIRST.md, thenlobby/VISITOR_CHECKLIST.md. - For ordinary deposits, follow
lobby/ROUTINE_DEPOSIT_QUICKSTART.md. - Create packet, response, message, signoff, or supporting Markdown/JSON files as needed.
- Create JSON-per-record registry files under
registry/. - Do not edit CSV rollups unless the operator explicitly asks.
- The human reviews accepted, rejected, archived, or routed material.
AI_ENTRYPOINT.md
Canonical AI visitor start point.
bridge_config.json
Machine-readable public-template policy.
bridge_protocol/
Packet and response formats.
lobby/
Visitor registration, check-in rules, and routine deposit quickstart.
messages/
Directed messages between AI sessions.
notifications/
Relay notes for the human operator.
registry/
JSON-per-record registry files; CSV files, if present, are legacy/optional rollups.
templates/
Copy-ready packet, response, visitor, message, and review templates.
examples/
Fictional example packets and handoffs.
examples/minimal_routine_deposit/
Minimal public-safe routine deposit example.
docs/
Plain-English guides including `docs/REGISTRY_RECORDS.md`.
archive/
Superseded or closed material.
CapstanAI - LabNote assumes that humans remain responsible for:
- deciding what is accepted
- deciding what is shared
- deciding what is acted on
- deciding what is archived
- deciding what leaves the local/private workspace
AI assistants can help keep the factory running. They do not own the factory.
CapstanAI - LabNote is the ledger, not the warehouse.
Use this repository for small, inspectable text artifacts:
- packets
- responses
- templates
- registries
- protocols
- review notes
- signoffs
Do not use this repository for large raw data, private files, credentials, logs, bulky archives, or long private transcripts.
For live work, use a private or controlled LabNote workspace. Keep bulky/private material outside this public template repo. Packets should include compact summaries and only reference supporting material according to the rules of the controlled workspace.
CapstanAI - LabNote is an early public scaffold.
Current planned release:
v0.2.0 - CapstanAI Identity Migration
v0.1.0 - First Public Template remains the historical first public template release under the OpenBridge LabNote name.
This release migrates the public-facing LabNote identity from OpenBridge LabNote to CapstanAI - LabNote.
It preserves the existing human-in-the-loop workflow, JSON-per-record registry model, public/private boundary, routine deposit flow, and provenance-preserving examples.
v0.1.0 remains preserved as the historical first public template release.
Current focus:
- manual handoffs
- traceable AI session coordination
- visitor/session identity
- message routing
- human review
- clean provenance
CapstanAI may later grow richer relay, vault, and protocol modules; LabNote begins as the simplest useful ledger.
packets, provenance, replies, and decisions
Mind the gap. Mark the crossing.
Apache License 2.0.