The system isn't three separate tools — it's three layers with defined roles, explicit data flows, and bidirectional checks that keep them in sync. D1 is the source of truth for operational data. Memories hold the big picture. Project files hold the stable playbook. Skills are the glue that pull from all three.
Identity, current state, behavioral rules, architecture decisions. The stuff that rarely changes. Reserved for big-picture context — not operational data.
Playbook and stable reference. Org charts, skill scripts, deploy notes, lessons learned. Changes when your job or systems change, not daily.
Live operational data — tasks, people, tribal knowledge, relationship intel. Source of truth. Claude reads and writes via API every session.
Migration rules — data moves between layers on a cadence, not randomly:
Each skill is a markdown file with step-by-step instructions Claude follows exactly. The critical design rule: every skill explicitly declares which data sources it pulls from and in what order. Skills don't just read one layer — they consult all three, reconcile conflicts, and write back.
/morningDaily, before first meetingPull D1 stats, read project lessons file, compare memories against D1 counts, flag cold relationships/debriefAfter every meetingPull transcript, extract tasks and people intel, present for review, push approved items to D1/closeEnd of each sessionCapture decisions, run bidirectional drift check (D1 ↔ memories), update state across layers/weeklyFridayFull semantic audit — contradictions, stale data, orphaned references, relationship gaps, duplicates/grill-meBefore executing any planStress-test a plan or design — Claude interviews you one question at a time, walking each branch of the decision tree with its recommended answerThese markdown files live inside a Claude Project. They give Claude persistent context about the job, people, infrastructure, and repeatable workflows. Claude reads them at the start of every conversation — like onboarding docs for a hire that never forgets.
| File | Purpose |
|---|---|
| Reference — loaded first, every session | |
| ref-context.md | Who I am, career trajectory, daily cadence, what to watch for |
| ref-project-instructions.md | API endpoints, credentials, key people, facility context, commands |
| ref-eaton-stable.md | Stable reference pruned from memories — org chart, PPE rules, shift supervisors |
| ref-debrief-protocol.md | Post-meeting extraction format and strategic analysis structure |
| Skills — slash commands Claude executes like scripts | |
| skill-morning.md | /morning — pull stats, surface overdue, check drift, flag cold relationships |
| skill-debrief.md | /debrief — extract tasks and intel from transcript, review gate, push to database |
| skill-close.md | /close — capture decisions, drift check, update state across all three layers |
| skill-weekly.md | /weekly — full audit: contradictions, stale data, duplicates, drift |
| skill-grill-me.md | /grill-me — stress-test plans by walking every branch of the decision tree |
| skill-1on1-prep.md | /1on1-prep — 1-on-1 meeting prep with open items and talking points |
| skill-audit.md | /audit — semantic audit and drift scan across the whole system |
| Knowledge base — what doesn't exist in any official system | |
| kb-tribal-knowledge.md | Legacy snapshot — live data now in D1 database via API |
| kb-people-intel.md | Legacy snapshot — relationship dynamics now in D1 via API |
| kb-lessons.md | Dead ends and mistakes only. Force-read every morning to prevent repeats. |
| Infrastructure — the code that connects everything | |
| infra-worker-api.mjs | Live Cloudflare Worker source — the API Claude reads and writes to |
| infra-deploy-notes.md | Deploy patterns, gotchas, credential locations |
| Tools — interactive artifacts | |
| tool-floor-form.jsx | Mobile React form for machine walkthrough data collection |
| tool-1on1-coach.jsx | Interactive 1-on-1 meeting prep coach (API-powered) |
| Meta | |
| 00-index.md | This file list. Naming convention, rules, what goes where. |
Nothing hits the database without approval. Claude extracts, you review, then it pushes. This single rule prevents most of the problems people run into with AI assistants.
Drift check at close — every session ends with a bidirectional sync:
Compare task counts, WSRA progress, people count in memories against what D1 actually holds. Flag mismatches before the context window closes.
Check if decisions or state changes from this session need to be written to D1 before the chat ends. Catch orphaned work.
Three data stores means three places that can get out of sync. Without automated checks, you'll discover drift at the worst time — mid-conversation when a wrong number leads to a wrong decision.
Lightweight check built into /morning. Compares memory claims against D1 counts (task totals, people count, key metrics). Also flags orphaned task references and cold key relationships. No extra API calls — uses data already pulled for the brief.
Bidirectional comparison built into /close. Runs after every session. Catches both directions: D1 drifting from what memories claim, and session work that hasn't been written to D1 yet.
/weekly runs the deep scan: contradictions between layers, intel conflicts, orphaned references, duplicate records, stale knowledge, memory drift, and cold relationships. Stores a baseline to D1 for trend tracking.
When the API is down mid-conversation: buffer failed writes in the chat, degrade to memories + project files for context, flag the failure at close, recover and replay buffered writes next session. Don't lose work just because the database is unreachable.
Claude's in-app artifacts don't survive closing the app. It creates a new instance every time. Anything that needs to persist goes to an external host or gets exported before the session ends.
Claude will assign you tasks that were merely mentioned in conversation, not directed at you. Build a review gate — nothing hits the database without explicit approval. Default ambiguous items to FYI.
Otter, Whisper, and other transcription tools frequently get names wrong. Always search for name variants before creating a new person record or you'll create duplicates.
Move stable reference out of memories into project files. Memories should hold identity, current state, behavioral rules, and architecture decisions — not org charts or shift schedules. Prune monthly.
Your lessons file should capture dead ends and mistakes. The rest of the system tracks wins. The lessons file prevents repeat mistakes and gets force-read every morning.
Every debrief adds knowledge, every correction trains better behavior, every close catches drift, every weekly audit cleans what accumulated.
/morning — pull D1 stats, read lessons, lightweight drift scan, flag cold relationships/debrief — extract tasks and intel from transcript, review, push to D1/close — capture decisions, bidirectional drift check, sync all three layers/weekly — full audit: contradictions, stale data, duplicates, relationship gaps/grill-me — stress-test any plan before committing to itCreate a Claude Project. Add a context file (who you are, what you do, your daily rhythm), an index file, and one skill file for your most common workflow. This alone — before any infrastructure — makes Claude dramatically more useful.
Ask Claude to write a Cloudflare Worker with a D1 database. Start with tasks and people tables. Claude can write the Worker, the SQL schema, and walk you through the Cloudflare dashboard setup.
Add your Worker URL and auth token to your project instructions file. Now Claude can read from and write to your database during conversations. Start with a /morning skill that pulls your open tasks.
Add a bidirectional comparison to your /close skill from the start. Memory claims vs D1 reality, session work vs database state. Drift is invisible until it causes a bad decision — catch it every session instead.
Connect a transcription tool (Otter.ai, Granola, or manual paste). Build a /debrief skill that extracts tasks and knowledge from meetings — with a review gate. Every meeting now feeds the system.
Ask Claude to build a single-file HTML dashboard that pulls from your API. Deploy to Netlify. This gives you a visual view of everything Claude manages — but only after the data pipeline is solid.