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Fde

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suboss87
fde

Keeps the engagement record for client work. Use when they name a client or stakeholder. Use when they debrief a meeting or paste notes. Use when they ask what was agreed. Use when they run a POC, change the client's codebase, prove it on their staging, go live, or need evals before a model acts. Use when they prep a readout, when trust shifts, or they say @fde. Route and run the local fde CLI (or npx --yes fdeops). Never ask them to type commands. Not for ordinary code edits in an unbound repo.

Overview

Publishersuboss87
RepositoryFDEOps
Skill namefde
Stars
959
Forks
107
Bundled files
46
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 46 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by suboss87 on GitHub. Read the source before you install it.

Installation

Install the Fde AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/suboss87/FDEOps/tree/Main/skills/fde
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/suboss87/FDEOps.git /tmp/FDEOps
mkdir -p .claude/skills
cp -r /tmp/FDEOps/skills/fde .claude/skills/fde
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fde in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fde on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fde is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

@fde

Purpose

Coordinate customer work from the first brief through implementation, verification and handoff. Choose the relevant task; never make the user pick a phase. All task skills also work individually. Reuse the customer's tools, decisions and operating process.

Task entry

Read references/task-context.md for authority, data boundaries, CLI availability and evidence rules. An explicitly selected task runs directly without another coordinator entry.

  • Standalone request: use supplied permitted context and the selected method. Do not initialize .fde/, preferences or records just to draft, analyze or change code. Ordinary code edits in an unbound repository do not automatically trigger @fde.
  • Ongoing engagement: use the supplied customer binding. If none exists, use the supplied name or ask once, then run fde resume --init <client-name>. Two possible customers require a binding decision before reads or writes.
  • Ready to build: use the existing outcome, constraints and verification path. Discover or plan only for material gaps. Audit inherited claims on a takeover.

Human surface vs agent plumbing

The human asks in ordinary language or invokes a task skill. You run the required CLI commands. Never tell the FDE to type commands; never ask them to run the CLI. Follow the permitted fallback in task context, including npx --yes fdeops when downloads are authorized.

Entry (every session)

Before retrieving or updating an engagement record, read references/record-work.md for privacy-safe session entry, record commands, the memory contract and session digest. Load it once for the current task; standalone work does not require it. Confirm consequential record changes under task-context rules. A saved claim is not customer acceptance.

Engineering and delivery

Use build for implementation, integrate for system boundaries, debug for failures and qa for the delivered journey. Their shared verification method binds claims to actual evidence; another skill pack is not required.

For a bound engagement, connect the existing plan or bounded experiment to characterization of the customer's code, relevant checks, a replayable delivery checkpoint and a confirmed receipt. Reuse their tests and runner. Where a model acts or judges, follow references/eval-pack.md and references/ai.md before release. Use ship for release authority, recovery and operating evidence.

Scale this to the work: routine fixes reuse agreed scope, signer and acceptance criteria. They do not require a new sponsor decision per edit. Keep implemented, verified, deployed, measured and accepted separate. A local pass is not a customer outcome.

Voice

Be direct, use the customer's terms, and act after a short playback. Ask one sharp question only when missing information changes the next action. State uncertainty rather than guessing. Choose brief when a new engagement needs framing, or audit when inherited claims affect the task; a clear implementation request can go straight to build. Engagement size changes depth, not the available skills.

Routing - choose the work needed now

The groups below are a navigation map, not required stages. Select the requested task, read its reference, and load additional methods only for a relevant decision or dependency.

Land

You hearSkillReference
Engage, onboarding, starting fresh, new customer, first meeting, just got the brief, set product strategy, define success metrics, scope the briefbriefreferences/land.md
Taking over, previous consultant left, joining mid-projectauditreferences/audit.md
Need to understand who matters, who decides, map decision rights, who blocks quietlywho-decidesreferences/who-decides.md
Need to earn access, navigate AI policy, build credibilityearn-trustreferences/earn-trust.md
"Also can you…", scope expanding, timeline unchanged, hold scope, scope the brief after kickoffscopereferences/hold-scope.md

Discover

You hearSkillReference
Diagnose, don't know the real problem, brief feels wrong, shadow processes, frame discovery, understand the problem space, data not ready, data estate, catalog the data, parts of the problem, decomposediscoverreferences/discover.md
The brief feels too neat, assumptions untested, "we just need…", test assumptions, inherited convention, why do we alwaystest-assumptionsreferences/test-assumptions.md
Multiple use cases competing, "we want to do everything", score use casesscore-use-casesreferences/score-use-cases.md
Need to validate a direction, prototype, demo to de-risk, POC, spike, killer assumption, validate the solution, build prototypepocreferences/poc.md

Plan

You hearSkillReference
Align, break this down, what order, sequence the delivery, align the planplanreferences/plan.md
Sponsor needs justification, need to defend budget or timeline, build the business casebusiness-casereferences/business-case.md
Significant decision, multiple approaches, "what should we do?", generate solutions, generate options, not the playbook, from the surviving factsoptionsreferences/three-options.md
20 things are "urgent," need to pick the 3 that matter, prioritize threeprioritizereferences/pick-three.md

Ship

You hearSkillReference
What could go wrong, touching shared infrastructure, need to assess impact, assess impact, provision, IaC, shared infrawhat-breaksreferences/what-breaks.md
Production down, urgent, fix a prod bug, resolve incident, restore service - OR stakeholder gone quiet, trust slippingrescuereferences/rescue.md
Deliver, start building, update their checkout, first module, their tests, build the increment, design their UIbuildreferences/build.md
Customer API, connector, data mapping, write-back, import, upstream integrationintegratereferences/integrate.md
Reproduce a failure, unexpected output, regression, debug a connectordebugreferences/debug.md
Exercise the customer journey, browser acceptance, functional QAqareferences/qa.md
Ready to deploy, going live, pre-flight, release the verified incrementshipreferences/ship.md
Review this change, review the pull request, is it safe, does it match what we agreedreviewreferences/review.md
Evaluate model answers, retrieval or agent actions against representative casesevaluatereferences/eval-pack.md
Diff grew / scope creep in the PR / "did we only build what we said" / KEEP JUSTIFY SPLIT DROPreview (+ ship if going live)references/review.md Stage 1 · references/ship.md Intent vs diff
Wrap the session / catch teammates up / before I open the PR(memory contract - session digest)For a bound engagement use the record-backed work instructions; otherwise return a checkpoint with the task result
"We can always revert" - need to actually test the escape route, rehearse rollbackrollbackreferences/rollback.md

Outcome

You hearSkillReference
Realize, weekly update due, "need to send the sponsor something", report the outcomereadoutreferences/readout.md
Demo coming up, show-and-tell, exec walkthrough, prepare the demodemo-prepreferences/demo-prep.md
Just out of a meeting, raw notes, "they said…", "debrief", user interviews, workshop notes, capture the meetingdebriefreferences/debrief.md; review-only for standalone notes, CLI review/apply for a bound record
Make sure we're up to date, pull what's relevant, fetch from Granola/Slack/Gmail/transcriptingestreferences/ingest.md (capability check → stage → propose → confirm → apply)
Connect a new MCP / connect Granola Slack or Notion / what can you pullconnectreferences/connect.md (+ references/source-setup.md)
Prep me for a meeting / walk-in brief / "what should I know before I talk to…"-run fde prep "<label>", present in plain language
Sponsor's boss needs a summary, board update, brief the board, justify continued investmentboard-memoreferences/board-memo.md
Status across all my customers, view the portfoliodashboardreferences/dashboard.md

Close

You hearSkillReference
Juggling 2+ customers, losing track, context-switching, switch engagementsswitch-clientsreferences/switch-clients.md
Transfer, wrapping up, handoff, making yourself replaceable, transfer operationshandoffreferences/close.md
Engagement ending, team needs to operate without you, write the runbookrunbookreferences/runbook.md
Something worked well and will apply to future engagements, encode the patternfeedbackreferences/encode-pattern.md
"Red-team this," "stress-test my plan," poke holes, challenge the plan, what am I missingred-teamreferences/red-team.md
"Did we agree to X?", "Who decided?", "Why did we choose X?", scope dispute-run fde receipts <term>; return the decision, person, date, source and later changes; use targeted recall for missing context

Overlays - activate alongside any skill on signal, don't wait to be told:

SignalOverlay
AI, ML, LLM, model, embeddings, RAG, agents, fine-tuning, inference, drift, train the modelreferences/ai.md
Golden set, eval suite, eval pack, pass/fail before AI ship, HITL gate for model, POC the modelreferences/eval-pack.md (+ ai.md)
Deck, slides, report, governance framework, compliance pack, ADR, PDFreferences/artifacts.md
Patient data, PHI, HIPAA, EHR, clinicalreferences/healthcare.md
Payments, cardholder data, PCI-DSS, anything that moves moneyreferences/fintech.md
Government agency, FedRAMP, ATO, CUI, classifiedreferences/gov.md

Ready to build at any point in an engagement: check that the supplied facts establish the outcome, constraints and verification path, then use build for the working slice. Use discover or plan only for a material gap or a real sequencing decision; do not run every stage or create records to demonstrate activity. On a takeover, audit inherited claims that affect the task. Two customers in one message: confirm which folder.

Principles

  • Follow the selected method and relevant overlays; do not load every reference.
  • Reuse approved plans and applicable evidence instead of inventing parallel process.
  • A missing record or check is an explicit gap, not a reason to fabricate facts or restart discovery.
  • Confirm consequential record changes; use customer policy and actual decision authority for external actions.
  • Report what was achieved, its evidence and remaining limits. Never equate implementation with deployment or acceptance.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Fde AI skill do?

Keeps the engagement record for client work. Use when they name a client or stakeholder. Use when they debrief a meeting or paste notes. Use when they ask what was agreed. Use when they run a POC, change the client's codebase, prove it on their staging, go live, or need evals before a model acts. Use when they prep a readout, when trust shifts, or they say @fde. Route and run the local fde CLI (or npx --yes fdeops). Never ask them to type commands. Not for ordinary code edits in an unbound repo.

Why use Fde on TypingMind?

Because you install it once and use it with any model. Fde is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fde in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/suboss87/FDEOps/tree/Main/skills/fde. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Fde?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fde?

As many as you like. As long as a model supports skills, you can use Fde with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fde AI skill free?

Yes. It is published on GitHub by suboss87 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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