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The Marble — persistent memory and session handoff for AI agents

Marble Manual v3

verify

TheMarble

The problem: AI agents inherit context they can't source — a summary from three sessions ago comes back as fact. A confident wrong memory is worse than no memory.

What this is: A manual and six working specimens for agent memory hygiene: split tended from raw, label authority (ground / pressure / warning), gate writes to trusted ground, and prove refusal with hostile tests. Not a prompt pack. Not a product. Runnable evidence.

Prove it in three minutes:

cd EXAMPLEmarbles/trench/tests && node run-all.mjs

In plain engineering terms: conventions plus enforced gates for AI-agent memory and handoff. Stored context gets a tended/raw split and authority labels (ground / pressure / warning); writes to trusted ground pass through executable crossings that refuse bad records; hostile test suites prove the refusals are real. Six example implementations, 120 tests across four suites, all runnable from this tree:

./verify_examples.sh        # Linux/macOS — or .\verify_examples.ps1 on Windows

The rest of this repo wraps that machinery in its own working vocabulary. A marble is a model-facing continuity environment: a small inheritable place for recurring AI work. This pack is the manual layer — laws, process, specimens, and verification — not a shipped application.

New here? START_HERE.md — ten minutes, three steps, one cold judge demo.

Skeptical? Don't skim this pack and move on. Read FABLE_5_LIGHTHOUSE_EXCERPTS.md first (~15 min) — the turns that reframe the whole pack. Start with Turn 18 and Turn 37. Full sanitized build log: FABLE_5_LIGHTHOUSE_FULL.md or EXAMPLEmarbles/lighthouse/ancestry/conversation.md. A summary is not evidence.

Maintainer notes? PUBLISH.md — what ships, what's excluded, how to verify and re-sanitize ancestry.

Main sentence

A prompt gives the model instructions.

A marble gives the next model working conditions.

What problem does this solve?

Long-term memory for LLM agents that doesn't rot. If your AI assistant forgets everything between sessions — or worse, misremembers — this pack is a set of conventions and enforced gates for agent memory, context persistence, and handoff between context windows. It labels stored context by provenance (user-decided vs. model-inferred vs. unverified), gates writes to trusted memory through code that can refuse bad records, and proves the refusals with hostile test suites. It works with any model or harness: Claude, GPT, Gemini, Cursor, Codex, Claude Code.

Why would you want one?

You already have this problem; you just know it by other names.

  • Your agent confidently remembers something wrong. A summary from three sessions ago comes back as fact. A model's guess got written down, and now every future session inherits it as if you said it. A marble labels stored context by where it came from — user-decided, model-inferred, unverified — so the next session can tell ground from guesswork. (The manual calls this false ground; it's the one law every marble enforces.)

  • Your CLAUDE.md / memory file rots. It grows, drifts, contradicts the code, and no one notices because nothing checks it. A marble splits tended from raw: raw material is kept but never trusted; anything promoted to trusted ground passes a gate that can refuse — and the refusal is a test you can run. (See trench — seven tests on one gate.)

  • Every new session starts from zero, or worse, from a stale transcript. Cold starts are expensive; inherited transcripts are misleading. A marble's handoff separates decided / open / do-not-trust-yet / do-first, so the next arrival — tomorrow's session, a different model entirely — starts from labeled conditions instead of archaeology. (Six specimens were built by four different models for exactly this reason.)

  • Long-running work outlives any one context window. Research across weeks, a legal reference desk, a fiction canon, a personal memory system — anywhere "the model forgot" is less dangerous than "the model misremembers." (See lighthouse for truth-under-pressure, reference_desk for a domain example, cabin for a full memory engine.)

If none of these have bitten you yet, you may not need a marble. Bookmark it for the day one does.

Layout

marble_starter/
  START_HERE.md              stranger path — ten minutes to verify the claim
  FABLE_5_LIGHTHOUSE_EXCERPTS.md perspective lens — five turns (~15 min; read first)
  FABLE_5_LIGHTHOUSE_FULL.md     full Fable 5 build log (805 turns; audit only)
  AGENTS.md                  arrival seat for models building a marble
  README.md                  this file
  LETTER_TO_YOU_BOTH.md  non-technical note for builders
  Manual/                core manual trilogy
  Reference/             review harness + friction shelf (ADVANCED_MARBLES)
  EXAMPLEmarbles/        specimen marbles — see EXAMPLEmarbles/README.md
  TestData/                  optional external test packs
  verify_examples.ps1        run all specimen test suites (Windows)
  verify_examples.sh         run all specimen test suites (Linux/macOS, CI)
  PUBLISH.md                 public release notes and privacy checklist

Files

Path Role
START_HERE.md ten-minute stranger path — verify before you read everything
FABLE_5_LIGHTHOUSE_EXCERPTS.md Fable 5 perspective lens — five turns that reframe the pack (~15 min)
FABLE_5_LIGHTHOUSE_FULL.md Full Fable 5 build log — audit only; read excerpts first
AGENTS.md arrival seat for models using this manual pack
Manual/MANUAL.md conceptual manual and core laws
Manual/PROCESS.md build rhythm and pre-build note
Manual/TECHNICAL.md metaphor-to-mechanism bridge
Reference/REVIEW_TEMPLATE.md review harness
Reference/ADVANCED_MARBLES.md Friction shelf — consult when strain returns; §1 symptom table first (not a starter read)
PUBLISH.md public release notes — what ships, verify, re-sanitize ancestry

Example marbles

Full lineup, one-liners, which model built each, and why cross-model success matters → EXAMPLEmarbles/README.md.

Six marbles, four builders (Cursor, Codex, Claude Code, Claude Fable 5) — each landed an operable first pass with the same bones: forbidden cell, crossing, hostile test, handoff. The cross-model proof is not prose in this README: read FABLE_5_LIGHTHOUSE_EXCERPTS.md first; full log at lighthouse/ancestry/conversation.md.

Marble Path Built with Notes
Bench EXAMPLEmarbles/bench/ Cursor law on paper
Trench EXAMPLEmarbles/trench/ Codex one door in code — SHOWCASE.md
Fall EXAMPLEmarbles/fall/ Cursor breath router — SHOWCASE.md
Reference desk EXAMPLEmarbles/reference_desk/ Codex legal continuity specimen
Cabin EXAMPLEmarbles/cabin/ Claude Code full engine — 31 hostile tests
Lighthouse EXAMPLEmarbles/lighthouse/ Claude Fable 5 FABLE_5_LIGHTHOUSE_EXCERPTS.md — then SHOWCASE.md

Related repos

Not part of this pack — no verify_examples sweep here. Optional next steps once the manual and specimens make sense.

Repo Role
The Forest Provenance-aware memory spec for AI agents — SQLite schema + constitution. Similarity can retrieve; only ceremony can promote. Cabin's forest cousin; the spec FOREST.md is designed to be copied.
The Inn A writer's marble built in public — signed memory, adopted canon, nothing deleted. The history is the curriculum. Implements Forest under friction; build logs in logs/.

Use

Give this folder to a fresh model and ask it to build a marble for a recurring kind of work.

The model should not build immediately. It should first write a Pre-Build Note, find the cost, name the forbidden cell, choose a place, and only then build the smallest manual-operable first pass.

Status

Mine it. Do not worship it.

Examples are evidence, not a product brochure. Trust the commands and tests over any summary, including this file.

One honest caveat: every review of this pack to date has been by AI instances — and a framework written for models is exactly the kind of thing models are inclined to like. The tests don't care about prose, but the significance claims have not yet faced human eyes or field use. Human reports — especially negative ones — are the missing evidence, and welcome.

License

MIT

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Persistent memory and session handoff for AI agents — provenance-labeled context, gated writes that can refuse, hostile test suites. Manual + six working examples.

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