by suboss87
The discipline and methodology for Forward Deployed Engineers. 34 skills, deterministic CLI, self-writing engagement memory. Works with any AI coding tools.
# Add to your Claude Code skills
git clone https://github.com/suboss87/FDEOpsFDEOps is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by suboss87. The discipline and methodology for Forward Deployed Engineers. 34 skills, deterministic CLI, self-writing engagement memory. Works with any AI coding tools. It has 51 GitHub stars.
FDEOps's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/suboss87/FDEOps" and add it to your Claude Code skills directory (see the Installation section above).
FDEOps is primarily written in JavaScript. It is open-source under suboss87 on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh FDEOps against similar tools.
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The discipline and methodology for Forward Deployed Engineers.
You embed at a client site. You bridge strategy and code. You ship on their systems, not yours.
Every morning you open your AI coding agent, and it has no idea what happened yesterday with your projects/clients. You re-paste the same context. You explain the stakeholders again. You remind it about the scope change from Tuesday. Meanwhile, the real problem the one the brief didn't mention - sits undiscovered because nobody asked the right questions on day one.
fdeops fixes this. One @fde command gives your AI coding agent a complete engagement methodology, a memory that writes itself, and a co-pilot that never assumes. Describe your situation, the agent confirms its understanding, generates specs where needed, and runs the right method from first stakeholder meeting, discovery workshops to final handoff. Tomorrow's session opens with a state summary and the one thing worth your attention.
Claude Code
/plugin marketplace add suboss87/fdeops
/plugin install fdeops@fdeops
Cursor · Codex · Copilot · Gemini CLI
npx fdeops adapters .
Local LLMs - load skills/fde/SKILL.md as system prompt (guide)
npx fdeops init my-client # creates engagement memory
export FDEOPS_ENGAGEMENT=~/fde-engagements/my-client/.fde # point your tool at it
Creates 12 markdown files at ~/fde-engagements/my-client/.fde/ - private to your machine, never uploaded.
@fde I just got the brief. New client, payments platform, 3-week timeline.
Describe what's happening and the agent picks the right method. No configuration files to edit. No API keys. See docs/USAGE.md for the full workflow.
Requires: Node.js >= 18 (for CLI and adapters). Claude Code plugin install does not require Node separately.
Other install methods:
npx skills add suboss87/fdeops(Skills CLI) orgit clone https://github.com/suboss87/fdeops.git && cd fdeops && node bin/install.js(manual). Full install details: docs/install.md.
| You are... | What fdeops does for you |
|---|---|
| Forward Deployed Engineer | The role this was built for. 35 skills across the full engagement lifecycle - land, build, ship, close. |
| Consultant or contractor at a client site | Every session, you re-explain context. fdeops remembers for you. |
| Solutions architect bridging strategy and code | You navigate politics AND architecture. fdeops has methods for both. |
| Agency engineer running 3-5 clients | Client details blur together. One .fde/ per customer, never cross-contaminated. |
| Technical founder doing client work solo | You ARE the team. The agent becomes your second brain. |
flowchart LR
A["@fde"] --> B{"Describe\nyour situation"}
B --> C["Embed & Trust"]
B --> D["Discover & Diagnose"]
B --> E["Plan & Align"]
B --> F["Build & Guard"]
B --> G["Ship & Verify"]
B --> H["Operate & Close"]
C --> I[".fde/ memory\n(written as you work)"]
D --> I
E --> I
F --> I
G --> I
H --> I
I --> J["Next session\nloads automatically"]
Works with Claude Code - Cursor - Copilot - Devin - Gemini CLI - Ollama - LM Studio - any model that reads a markdown file
| Without fdeops | With fdeops | |
|---|---|---|
| Monday morning | Re-paste last week's context, explain the stakeholders again | Agent opens with "last session you were on the ingest retry - CTO demo is Friday" |
| Scope creep | Five "small" additions absorbed silently, timeline slips | Receipts timestamped - you walk into the sponsor meeting with evidence |
| Multiple customers | Wrong client name in a status update, details blur | One folder per customer, context-switch protocol, cross-contamination checklist |
| The sponsor meeting | "We completed the API endpoint" | "Manual reconciliation dropped from 3 FTEs to 0.5 - here's the rollback if it turns" |
| Before building | AI builds what it thinks you meant, surprises in the PR | Agent generates the spec first, you approve in one word, zero surprises |
| Domain | Skills | What it covers |
|---|---|---|
| Embed & Trust | land, audit, stakeholder-radar, trust-engineering, scope-defense | First days: access, credibility, scope |
| Discover & Diagnose | discover, assumption-audit, use-case-scoring, sketch | Finding the real problem behind the brief |
| Plan & Align | plan, business-case, options-analysis, initiative-triage | Sequencing work, getting sponsor alignment |
| Build & Guard | build, incremental-build, test-on-legacy, blast-radius, debug, rescue, security-audit, observability | Building safely on their codebase |
| Ship & Verify | ship, review, rollback-drill, qa-live | Getting to production without surprises |
| Operate & Close | status, demo-prep, debrief, exec-narrative, dashboard, multi-customer-ops, close, handoff-engineering, pattern-extract, red-team | Running and ending the engagement well |
Overlays activate automatically when your engagement involves AI projects, executive reporting, fintech, healthcare, or government compliance.
Full skill details: docs/skills-reference.md
.fde/)Your fieldbook - one per client, private to you, plain markdown:
| File | Role | Written by |
|---|---|---|
context.md |
Where you are; loaded first every session | every phase + session-stop hook |
brief.md |
What they said - hypothesis until discover | land |
success.md |
Done, measured, signed-off by whom | land |
reality.md |
The real problem, with evidence | discover / audit |
terrain.md |
Codebase map: hotspots, test gaps, AI components, data estate | discover / audit |
stakeholders.md |
Champions, resistance, trust signals | land, updated continuously |
trust-profile.md |
Sacred data, AI policy, approval chain | land + overlays |
decisions.md |
Plan + choices + integration contracts + sizing | plan / build / review / rescue |
risks.md |
Live risk register | all phases |
delivery.md |
What shipped, business value, rollback, pulse, adoption metrics | build / ship |
Every claim is tagged with its source and date so you can defend it in front of skeptical stakeholders.
Your engagement toolkit - deterministic, offline, always available:
fde scan # day-1 recon: hotspots, test gaps, secrets, AI components
fde resume # initialize or resume an engagement
fde log # write decisions, risks, delivery, contacts
fde receipts # search memory with dates - "what did we agree about X?"
fde capture # session-end snapshot
fde status # portfolio triage across all customers (red > amber > green)
fde dashboard # render every engagement into one offline HTML fieldbook
One skill file powers every tool. Each adapter is a thin pointer at the same @fde skill - the methodology and memory stay consistent whether you use Claude Code, Codex, Cursor, Copilot, Gemini CLI, or a local model. Details: adapters/.
No cloud dependency. fdeops calls no external API. The AI skill is a markdown file your model reads. The CLI is local Node.js. Works fully offline, fully air-gapped, fully private. See
adapters/LOCAL-LLM.mdfor local model setup.
cd fdeops && git pull && node bin/install.js
Built and maintained by Subash Natarajan. Share your feedbacks via Issues - see CONTRIBUTING.md.
FDE Methodology - ATTRIBUTION.md - SECURITY.md - PRIVACY.md - [Repo layout](doc