FDEOps

Your AI coding agent forgets your client every morning. fdeops remembers.

One @fde skill over a local client notebook (the fieldbook under .fde/) - one folder per client. The system of record for embeds - Forward Deployed Engineers and anyone living on a client site from first meeting to handoff. Feels like a second brain; behaves like a defensible record (dated, sourced, yours). Works the same for consultants, agency developers, solutions architects, and fractional CTOs.

  land      discover      plan      build      ship      close
    |           |           |         |          |         |
    +-----------+-----------+---------+----------+---------+
          the fieldbook (.fde/) - one per engagement
             written as a side effect of the work

You talk in plain language with @fde. The agent (and an optional CLI) handles the boring memory work. You still confirm anything that goes into the record.

The week

Day to day you only need @fde and normal English. No command cheat sheet.

Same client folder every time (~/fde-engagements/<client>/.fde/). Your AI coding agent reads it on every session.

Quickstart

1. Install (pick one)

npx skills add suboss87/fdeops          # Cursor, Codex, and skills-compatible agents

/plugin marketplace add suboss87/fdeops # Claude Code
/plugin install fdeops@fdeops

2. Bind once - inside the client workspace (setup only; not a daily habit):

npx fdeops resume --init garvey   # creates ~/fde-engagements/garvey engagement + binds workspace

Check it worked:

npx fdeops resume                 # prints a short "where we are" for this client

3. Work - talk normally:

@fde I just got the brief. New client, payments platform, they want it live before their Q3 audit.

@fde routes and updates the fieldbook - you confirm judgment. Full workflow: docs/USAGE.md.

• Cursor / Codex / Copilot / Gemini CLI: npx fdeops adapters . - adapters/
• Local LLMs (Ollama, LM Studio, llama.cpp): load skills/fde/SKILL.md as the system prompt - guide
• Manual / air-gapped: git clone https://github.com/suboss87/fdeops.git && cd fdeops && node bin/install.js
• Try without install: npx fdeops scan - day-1 recon (heuristic leads, not findings)
• Requires: Node.js >= 18 for the CLI and adapters
• Advanced: FDEOPS_ENGAGEMENT overrides the workspace registry. Full matrix: docs/install.md

How it works

• You describe the situation with @fde (or plain language once the skill is loaded)
• Session start / end - small hooks load where you left off and capture what changed (no re-paste)
• Local CLI - memory writes, search, and status with no model tokens; the agent runs it. You do not need to learn it for daily use (docs/USAGE.md)

fdeops complements repo memory: CLAUDE.md holds how the code works; the fieldbook holds how the client engagement works.

Switch coding agents anytime

The fieldbook lives on disk at ~/fde-engagements/<client>/.fde/ - not inside Claude, Cursor, or any other tool. Change AI coding agents and the same client record is still there.

On the new tool:

1. Install @fde for that tool (plugin, npx skills add suboss87/fdeops, or npx fdeops adapters . - see adapters/)
2. Open a workspace already bound with npx fdeops resume --init <client> (or bind once if this checkout is new)
3. Talk with @fde or run npx fdeops resume

Same fieldbook. Claude Code gets the fullest ride (session start/stop hooks). Elsewhere the memory and CLI are the same; context usually loads when you ask @fde / resume, not automatically. Details: docs/install.md.

Overlays for regulated domains (AI, fintech, healthcare, government) activate on signal. Full matrix: docs/skills.md.

Engagement memory (.fde/)

The fieldbook is the system of record for the embed - one folder per client, plain markdown you can read, grep, and take with you:

Every entry is dated and sourced, so you can defend it in front of skeptical stakeholders. Schema: docs/schema.md.

Fieldbook UI

Open the system of record in a browser - trust, phase, next action, and the full record in one local page. Ask @fde for the dashboard, or run npx fdeops dashboard (current engagement by default; --all for the portfolio).

Who this is for

Your data stays yours

• Local only. Pure git + file reads - no network calls, no telemetry, no account. Works air-gapped.
• Plain markdown. No database, no lock-in.
• No new data path. The AI sees client code only when you point your agent at it. <private> tags are redacted from CLI/dashboard/hook output; do not feed raw private blocks into the model (file tools bypass that redaction).
• Nothing enters the record unreviewed. The model drafts, you confirm (fde debrief --dry-run shows the routing first); the hooks record only git facts. Your fieldbook stays yours to defend.
• Know your sync surface. ~/fde-engagements lives in your home directory - your backup and cloud-sync setup now covers client notes. fde resume --init warns if the folder sits in a synced path. Read PRIVACY.md before your first NDA'd engagement.

Details: PRIVACY.md · SECURITY.md

Principles

• The artifact is the memory - producing work and recording it are one action
• Methods, not autonomy - each skill tells you what to check; the judgment, the trust, and the consequences stay yours
• Brief is a hypothesis - discover before building the wrong thing
• Evidence on every claim - these files get defended in front of skeptical clients
• One customer, one folder - context never bleeds

Updating

# Plugin / skills install: re-run the install command from Quickstart
# From a git clone:
cd fdeops && git pull && node bin/install.js

Contributing

Built and maintained by Subash Natarajan. Share your feedback via Issues - see CONTRIBUTING.md.

Thanks to builders whose craft helped sharpen the thinking behind this kit, among them Andrej Karpathy's engineering guidelines and the agentic engineering workflow notes from David Ondrej / Michael Shimeles. FDEOps itself is handcrafted for field work; any resemblance is inspiration, not a fork.

FDE Methodology - SECURITY.md - PRIVACY.md - Repo layout - Skills matrix - MIT