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Mrl Deskbook

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jgsystemsconsulting
mrl-deskbook

Knowledge base from the Manufacturing Readiness Level (MRL) Deskbook (Version 2025, 1 May 2025, OSD ManTech / Joint Service/Industry MRL Working Group). Use for manufacturing maturity and producibility risk in defense acquisition: ten-level MRL scale (target, not grade); demonstration environments; nine Section 2.4 threads; Adaptive Acquisition Framework pathway targets; assessment-to-MMP loop; contract language (Section L/M, SOW, AS6500A, DIDs); criteria adaptation for S and T, sustainment and depot, limited systems including ships, and industry gates; and OT cybersecurity screening inside an assessment. Manufacturing-readiness focused: it measures producibility risk and frames mitigation; it is not a technology-readiness (TRL) guide, not a full systems-engineering process model, not a cost-estimating or schedule guide, and not a deep cybersecurity audit method (see sibling packs for those).

Overview

Publisherjgsystemsconsulting
Repositoryjgs-se-knowledge-packs
Skill namemrl-deskbook
Stars
121
Forks
1
Bundled files
13
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.

  • 13 bundled files

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

  • Open source

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

Installation

Install the Mrl Deskbook 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/jgsystemsconsulting/jgs-se-knowledge-packs/tree/main/packs/mrl-deskbook
  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/jgsystemsconsulting/jgs-se-knowledge-packs.git /tmp/jgs-se-knowledge-packs
mkdir -p .claude/skills
cp -r /tmp/jgs-se-knowledge-packs/packs/mrl-deskbook .claude/skills/mrl-deskbook
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mrl Deskbook 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 Mrl Deskbook 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 Mrl Deskbook 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.

Manufacturing Readiness Level (MRL) Deskbook (Version 2025)

Source: OSD Manufacturing Technology Program with the Joint Service/Industry MRL Working Group. US Government work, public domain under 17 U.S.C. 105; Distribution A, approved public release; DOPSR Case # 25-T-1829. Advisory best practice, not a DoD requirement. See LICENSE.

When to use

Use when a program, project, or supplier question is about manufacturing maturity, producibility risk, MRL targets on an acquisition pathway, running an MRL Assessment, writing a Manufacturing Maturation Plan, putting maturity into contract language, adapting criteria, or screening operational-technology cybersecurity on the shop floor.

Prerequisites: none. Plain Markdown. No MCP server, API key, or licence tier needed at runtime.

How to Use This Skill

  • No arguments: read the Chapter Index and open the chapter that matches the question.
  • Topic question (thread, environment, MMP, contract language, OT screening): use Topic Index chNN tokens.
  • Lifecycle question (MSA, TMRR, EMD, LRIP, FRP, MTA, UCA): start with ch03, then assessment and MMP chapters.

Chapter Index

ChFileJob
01ch01-mrl-deskbook-introduction.mdPurpose, organization, advisory status, Version 2025 structure
02ch02-mrl-deskbook-scale-threads-and-trl.mdScale, environments, nine threads, MRL and TRL
03ch03-mrl-deskbook-adaptive-acquisition-framework.mdMCA, MTA, UCA pathway targets
04ch04-mrl-deskbook-conducting-assessments.mdScope, taxonomy, team, self-assessment, site visit, report
05ch05-mrl-deskbook-maturation-plans-and-risk.mdMMP and risk-management practice
06ch06-mrl-deskbook-contract-language.mdPlanning, RFP, SOW, deliverables, quality, AS6500A
07ch07-mrl-deskbook-users-guide.mdExcel Users Guide use; workbook stays external
08ch08-mrl-deskbook-adapting-criteria.mdS and T, sustainment and depot, limited systems including ships, industry
09ch09-mrl-deskbook-ot-cybersecurity.mdOT screening inside a manufacturing assessment

Topic Index

  • Introduction and advisory status: ch01
  • Responsible organization and assessed organization: ch01
  • Ten-level scale and non-linear targets: ch02
  • Demonstration environments: ch02
  • Nine threads and sub-threads: ch02
  • MRL and TRL relationship: ch02
  • Adaptive Acquisition Framework pathways: ch03
  • MCA phase targets: ch03
  • MTA Rapid Prototyping and Rapid Fielding: ch03
  • UCA targets: ch03
  • Assessment scope and taxonomy: ch04
  • Self-assessment and site visit: ch04
  • Assessment report: ch04
  • Manufacturing Maturation Plan: ch05
  • Risk-management best practices: ch05
  • RFP Section L and Section M: ch06
  • SOW, DIDs, AS6500A: ch06
  • Users Guide workbook: ch07
  • S and T adaptation: ch08
  • Sustainment and depot adaptation: ch08
  • Single-system and ship adaptation: ch08
  • Industry gated development: ch08
  • Operational technology cybersecurity screening: ch09

Supporting Files

Scope and Limits

Manufacturing readiness and producibility risk for defense acquisition practice. This skill is not a technology-readiness (TRL) guide, not a full systems-engineering process model, not a cost-estimating or schedule guide, and not a deep cybersecurity audit method. Appendix A criteria matrix cells are not reproduced. The Excel Users Guide remains an external workbook. DoDI 5000.88, FAR, and DFARS are named only, never quoted.

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 Mrl Deskbook AI skill do?

Knowledge base from the Manufacturing Readiness Level (MRL) Deskbook (Version 2025, 1 May 2025, OSD ManTech / Joint Service/Industry MRL Working Group). Use for manufacturing maturity and producibility risk in defense acquisition: ten-level MRL scale (target, not grade); demonstration environments; nine Section 2.4 threads; Adaptive Acquisition Framework pathway targets; assessment-to-MMP loop; contract language (Section L/M, SOW, AS6500A, DIDs); criteria adaptation for S and T, sustainment and depot, limited systems including ships, and industry gates; and OT cybersecurity screening inside...

Why use Mrl Deskbook on TypingMind?

Because you install it once and use it with any model. Mrl Deskbook 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 Mrl Deskbook in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jgsystemsconsulting/jgs-se-knowledge-packs/tree/main/packs/mrl-deskbook. 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 Mrl Deskbook?

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 Mrl Deskbook?

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

Is the Mrl Deskbook AI skill free?

It is published on GitHub by jgsystemsconsulting. 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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