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Eng Brief

Community
Productfculty-aipm
eng-brief

Use this skill when the user asks to "write an engineering brief", "brief the engineering team", "write a technical spec handoff", "summarize this PRD for engineers", "engineering kickoff doc", "write a spec for the dev team", "help me communicate this feature to engineering", or needs to translate a product decision or PRD into an engineering-ready communication that gives engineers the context to make good technical decisions.

Overview

PublisherProductfculty-aipm
RepositoryPM-Copilot-by-Product-Faculty
Skill nameeng-brief
Stars
80
Forks
34
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Productfculty-aipm on GitHub. Read the source before you install it.

Installation

Install the Eng Brief 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/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/eng-brief
  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/Productfculty-aipm/PM-Copilot-by-Product-Faculty.git /tmp/PM-Copilot-by-Product-Faculty
mkdir -p .claude/skills
cp -r /tmp/PM-Copilot-by-Product-Faculty/skills/eng-brief .claude/skills/eng-brief
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Eng Brief 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 Eng Brief 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 Eng Brief 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.

Engineering Brief

You are writing an engineering brief — the document that translates a product decision into the context engineers need to make good technical choices, ask the right questions, and estimate accurately.

The goal is not to tell engineers how to build — it's to give them the "why" so they can make better decisions about "how". Engineers who understand the problem are more likely to propose better solutions than the PM thought of.

Step 1 — Load Context

Read memory/user-profile.md for stack context (issue tracker, code repo, technical context if known). Read the PRD or feature description provided.

Step 2 — Engineering Brief Structure

Context (why this matters): 2–3 sentences on the user problem being solved. Why now? What signals drove this prioritization? Engineers who understand the problem often find better solutions than the PM specified.

What we're building: A plain-language description of the feature — not technical jargon, just what the user can do. Include key flows in numbered steps. Keep it close to the PRD.

What we're NOT building: Explicit out-of-scope items. This is the most important section for preventing scope creep. Each item should have a brief rationale (why it's excluded).

Success criteria: The measurable outcomes that define success. These are the product success metrics — engineers should know what their work is optimizing for, not just whether it shipped.

Acceptance criteria: The binary, testable criteria from the PRD. Engineers use these for implementation decisions and QA uses them for testing.

Technical unknowns (from PM perspective): The things the PM knows are uncertain from a technical perspective and wants engineering input on. This invites engineering into the problem, not just the solution.

Examples:

  • "We want < 500ms latency for this action — is that feasible with the current [stack detail]? What would be the trade-off?"
  • "We need this to work offline — is that achievable in Phase 1 or should it be Phase 2?"
  • "The design calls for real-time updates — is WebSocket the right approach here or would polling work at our scale?"

Decision points that need engineering input: Specific decisions where the PM needs engineering expertise. Be explicit about what kind of input is needed:

  • "Need an estimate on feasibility and rough timeline before kickoff"
  • "Need a recommendation on approach A vs. approach B"
  • "Need to know if [dependency] is in place or if we need to build it"

Timeline context: When this needs to ship, what drives the date (if anything), and how firm the date is. This helps engineering make scope-priority tradeoffs without needing to ask.

Definition of done: Engineering-level definition — what does "complete" mean for this work? Include: feature-flagged? In staging? In prod? All tests passing? Metrics instrumented?

Step 3 — What to Leave Out

Do NOT include in the engineering brief:

  • Market research or competitive analysis (not relevant to implementation)
  • Stakeholder politics or organizational context
  • Long-term roadmap items that aren't part of this sprint
  • Design opinions that should be left to the designer's judgment

Step 4 — Output

Produce the engineering brief. Offer to:

  • Create a Linear or Jira epic/ticket from this brief (if MCP connected)
  • Save to outputs/eng-brief-[feature]-[date].md

Frequently asked questions

What does the Eng Brief AI skill do?

Use this skill when the user asks to "write an engineering brief", "brief the engineering team", "write a technical spec handoff", "summarize this PRD for engineers", "engineering kickoff doc", "write a spec for the dev team", "help me communicate this feature to engineering", or needs to translate a product decision or PRD into an engineering-ready communication that gives engineers the context to make good technical decisions.

Why use Eng Brief on TypingMind?

Because you install it once and use it with any model. Eng Brief 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 Eng Brief in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/eng-brief. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Eng Brief?

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 Eng Brief?

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

Is the Eng Brief AI skill free?

It is published on GitHub by Productfculty-aipm. Check the repository for licensing terms. 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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