Clarify operating model and project corpus state

This commit is contained in:
2026-04-06 07:25:33 -04:00
parent 5069d5b1b6
commit 8a94da4bf4
4 changed files with 220 additions and 20 deletions

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@@ -86,6 +86,24 @@ file replication of the live machine store.
- OpenClaw must continue to work if AtoCore is unavailable
- write-back from OpenClaw into AtoCore is deferred until later phases
## Intended Daily Operating Model
The target workflow is:
- the human continues to work primarily in PKM project notes, Git/Gitea repos,
Discord, and normal OpenClaw sessions
- OpenClaw keeps its own runtime behavior and memory system
- AtoCore acts as the durable external context layer that compiles trusted
project state, retrieval, and long-lived machine-readable context
- AtoCore improves prompt quality and robustness without replacing direct repo
work, direct file reads, or OpenClaw's own memory
In other words:
- PKM and repos remain the human-authoritative project sources
- OpenClaw remains the active operating environment
- AtoCore remains the compiled context engine and machine-memory host
## Current Status
As of the current implementation pass:
@@ -95,6 +113,8 @@ As of the current implementation pass:
- the service is running from Dalidou
- the T420/OpenClaw machine can reach AtoCore over network
- a first read-only OpenClaw-side helper exists
- the live corpus now includes initial AtoCore self-knowledge and a first
curated batch for active projects
- the long-term content corpus still needs broader project and vault ingestion
This means the platform is hosted on Dalidou now, the first cross-machine

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@@ -5,7 +5,8 @@
AtoCore is no longer just a proof of concept. The local engine exists, the
correctness pass is complete, Dalidou now hosts the canonical runtime and
machine-storage location, and the T420/OpenClaw side now has a safe read-only
path to consume AtoCore.
path to consume AtoCore. The live corpus is no longer just self-knowledge: it
now includes a first curated ingestion batch for the active projects.
## Phase Assessment
@@ -41,6 +42,10 @@ path to consume AtoCore.
- Dalidou Docker deployment foundation
- initial AtoCore self-knowledge corpus ingested on Dalidou
- T420/OpenClaw read-only AtoCore helper skill
- first curated active-project corpus batch for:
- `p04-gigabit`
- `p05-interferometer`
- `p06-polisher`
## What Is True On Dalidou
@@ -67,10 +72,23 @@ The Dalidou instance already contains:
- Master Plan V3
- Build Spec V1
- trusted project-state entries for `atocore`
- curated staged project docs for:
- `p04-gigabit`
- `p05-interferometer`
- `p06-polisher`
- curated repo-context docs for:
- `p05`: `Fullum-Interferometer`
- `p06`: `polisher-sim`
Current live stats after the first active-project ingest pass:
- `source_documents`: 32
- `source_chunks`: 523
- `vectors`: 523
The broader long-term corpus is still not fully populated yet. Wider project and
vault ingestion remains a deliberate next step rather than something already
completed.
completed, but the corpus is now meaningfully seeded beyond AtoCore's own docs.
## What Is True On The T420
@@ -81,14 +99,41 @@ completed.
- `/home/papa/clawd/skills/atocore-context/`
- the T420 can successfully reach Dalidou AtoCore over network/Tailscale
- fail-open behavior has been verified for the helper path
- OpenClaw can now seed AtoCore in two distinct ways:
- project-scoped memory entries
- staged document ingestion into the retrieval corpus
## What Exists In Memory vs Corpus
These remain separate and that is intentional.
In `/memory`:
- project-scoped curated memories now exist for:
- `p04-gigabit`: 5 memories
- `p05-interferometer`: 6 memories
- `p06-polisher`: 8 memories
These are curated summaries and extracted stable project signals.
In `source_documents` / retrieval corpus:
- real project documents are now present for the same active project set
- retrieval is no longer limited to AtoCore self-knowledge only
This separation is healthy:
- memory stores distilled project facts
- corpus stores the underlying retrievable documents
## Immediate Next Focus
1. Use the new T420-side AtoCore skill in real OpenClaw workflows
2. Ingest selected active project sources in a controlled way
3. Define the first broader AtoVault/AtoDrive ingestion batches
4. Add backup/export strategy for Dalidou machine state
5. Only later consider deeper automatic OpenClaw integration or write-back
2. Tighten retrieval quality for the newly seeded active projects
3. Promote only the most stable active-project facts into trusted project state
4. Define the first broader AtoVault/AtoDrive ingestion batches
5. Add backup/export strategy for Dalidou machine state
6. Only later consider deeper automatic OpenClaw integration or write-back
## Guiding Constraints

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@@ -9,38 +9,67 @@ AtoCore now has:
- initial self-knowledge ingested into the live instance
- trusted project-state entries for AtoCore itself
- a first read-only OpenClaw integration path on the T420
- a first real active-project corpus batch for:
- `p04-gigabit`
- `p05-interferometer`
- `p06-polisher`
## Immediate Next Steps
1. Use the T420 `atocore-context` skill in real OpenClaw workflows
- confirm the ergonomics are good
- confirm the fail-open behavior remains acceptable in practice
2. Ingest selected active projects only
- start with the current active project set
- prefer trusted operational/project sources first
- ingest broader PKM sources only after the trusted layer is loaded
3. Review retrieval quality after the first real project ingestion batch
2. Review retrieval quality after the first real project ingestion batch
- check whether the top hits are useful
- check whether trusted project state remains dominant
4. Define backup and export procedures for Dalidou
- reduce cross-project competition and prompt ambiguity where needed
3. Promote a small number of stable active-project facts into trusted project
state
- active architecture
- current selected path
- key constraints
- current next step
4. Continue controlled project ingestion only where the current corpus is still
thin
- a few additional anchor docs per active project
5. Define backup and export procedures for Dalidou
- SQLite snapshot/backup strategy
- Chroma backup or rebuild policy
5. Keep deeper automatic runtime integration deferred until the read-only model
6. Keep deeper automatic runtime integration deferred until the read-only model
has proven value
## Recommended Active Project Ingestion Order
## Recommended Near-Term Project Work
The first curated batch is already in.
The near-term work is now:
1. strengthen retrieval quality
2. promote the most stable facts into trusted project state
3. only then add a few more anchor docs where still needed
## Recommended Additional Anchor Docs
1. `p04-gigabit`
2. `p05-interferometer`
3. `p06-polisher`
For each project:
P04:
1. identify the matching AtoDrive/project-operational sources
2. identify the matching PKM project folder(s)
3. ingest the trusted/operational material first
4. ingest broader notes second
5. review retrieval quality before moving on
- 1 to 2 more strong study summaries
- 1 to 2 more meeting notes with actual decisions
P05:
- a couple more architecture docs
- selected vendor-response notes
- possibly one or two NX/WAVE consumer docs
P06:
- more explicit interface/schema docs if needed
- selected operations or UI docs
- a distilled non-empty operational context doc to replace an empty `_context.md`
## Deferred On Purpose
@@ -56,5 +85,18 @@ The next batch is successful if:
- OpenClaw can use AtoCore naturally when context is needed
- AtoCore answers correctly for the active project set
- retrieval surfaces the seeded project docs instead of mostly AtoCore meta-docs
- project ingestion remains controlled rather than noisy
- the canonical Dalidou instance stays stable
## Long-Run Goal
The long-run target is:
- continue working normally inside PKM project stacks and Gitea repos
- let OpenClaw keep its own memory and runtime behavior
- let AtoCore supplement LLM work with stronger trusted context, retrieval, and
context assembly
That means AtoCore should behave like a durable external context engine and
machine-memory layer, not a replacement for normal repo work or OpenClaw memory.

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docs/operating-model.md Normal file
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@@ -0,0 +1,93 @@
# AtoCore Operating Model
## Purpose
This document makes the intended day-to-day operating model explicit.
The goal is not to replace how work already happens. The goal is to make that
existing workflow stronger by adding a durable context engine.
## Core Idea
Normal work continues in:
- PKM project notes
- Gitea repositories
- Discord and OpenClaw workflows
OpenClaw keeps:
- its own memory
- its own runtime and orchestration behavior
- its own workspace and direct file/repo tooling
AtoCore adds:
- trusted project state
- retrievable cross-source context
- durable machine memory
- context assembly that improves prompt quality and robustness
## Layer Responsibilities
- PKM and repos
- human-authoritative project sources
- where knowledge is created, edited, reviewed, and maintained
- OpenClaw
- active operating environment
- orchestration, direct repo work, messaging, agent workflows, local memory
- AtoCore
- compiled context engine
- durable machine-memory host
- retrieval and context assembly layer
## Why This Architecture Works
Each layer has different strengths and weaknesses.
- PKM and repos are rich but noisy and manual to search
- OpenClaw memory is useful but session-shaped and not the whole project record
- raw LLM repo work is powerful but can miss trusted broader context
- AtoCore can compile context across sources and provide a better prompt input
The result should be:
- stronger prompts
- more robust outputs
- less manual reconstruction
- better continuity across sessions and models
## What AtoCore Should Not Replace
AtoCore should not replace:
- normal file reads
- direct repo search
- direct PKM work
- OpenClaw's own memory
- OpenClaw's runtime and tool behavior
It should supplement those systems.
## What Healthy Usage Looks Like
When working on a project:
1. OpenClaw still uses local workspace/repo context
2. OpenClaw still uses its own memory
3. AtoCore adds:
- trusted current project state
- retrieved project documents
- cross-source project context
- context assembly for more robust model prompts
## Practical Rule
Think of AtoCore as the durable external context hard drive for LLM work:
- fast machine-readable context
- persistent project understanding
- stronger prompt inputs
- no need to replace the normal project workflow
That is the architecture target.