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Dod Mosa

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jgsystemsconsulting
dod-mosa

Knowledge base from the OUSD(R&E) guidebook Implementing a MOSA in DoD Programs (Feb 2025). Use for the Modular Open Systems Approach as a DoD acquisition + design discipline: the statutory/regulatory basis (10 U.S.C. 4401–4403, FY2017/FY2021 NDAA, DFARS), the five OUSD(R&E) pillars, the plan→modularize→identify→define→standardize interface lifecycle, technical levers (WBS/MIL-STD-881F taxonomy, standards profiling, API-first software, COTS/cybersecurity), MOSA assessment metrics and tools (PART/OAAT/KOSS/SEAM/MAUT), technology-change and DMSMS management, roadmaps, MOSA across the six AAF pathways, and contracting/IP/data-rights mechanics. SCOPE LIMITS: this is U.S. DoD weapon-system acquisition policy, not a general open-architecture or interface-standards reference — it names standards (FACE, OMS, DISR) without reproducing them, is light on detailed engineering of any specific standard, and does not cover the underlying SE processes (use dau-se-guidebook / nasa-npr-7123) or general systems-engineering theory (use sebok).

Overview

Publisherjgsystemsconsulting
Repositoryjgs-se-knowledge-packs
Skill namedod-mosa
Stars
121
Forks
1
Bundled files
11
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.

  • 11 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 Dod Mosa 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/dod-mosa
  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/dod-mosa .claude/skills/dod-mosa
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dod Mosa 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 Dod Mosa 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 Dod Mosa 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.

DoD MOSA — Implementing a Modular Open Systems Approach in DoD Programs

Source: OUSD(R&E), Implementing a MOSA in DoD Programs (Feb 2025, DOPSR 25-T-1210) — US Government work, public domain | Chapters: 7

When to use

Use this skill when a U.S. defense program must adopt, plan, write into contract, assess, or sustain a Modular Open Systems Approach: framing MOSA against the statute and DFARS, working the five pillars and the interface lifecycle, making the technical decisions (WBS taxonomy, standards profiling, software/cybersecurity), levying MOSA requirements across the AAF pathways, and tying it all to data rights, assessment metrics, and roadmaps. This is the DoD acquisition-policy companion to the SE-process packs (dau-se-guidebook, nasa-npr-7123) and the SE canon (sebok).

Prerequisites: none — plain Markdown; no MCP server, API key, or licence tier needed at runtime.

How to Use This Skill

  • Without arguments — load the core frameworks below: the statutory chain, the five OUSD(R&E) pillars, the interface lifecycle, and how MOSA is assessed and contracted.
  • With a topic — ask about a pillar (e.g. "certify conformance"), an interface-lifecycle step, a statute or DFARS clause, an assessment tool (PART, OAAT, KOSS, SEAM, MAUT), an acquisition pathway, data rights, DMSMS, or roadmaps.
  • With a chapter — ch01 (statute/policy), ch02 (pillars/benefits), ch03 (program-management/interface lifecycle), ch04 (technical considerations), ch05 (assessment/technology change/roadmaps), ch06 (acquisition pathways), ch07 (implementation appendices/tools/contracting).

Supporting files: glossary.md, patterns.md, cheatsheet.md.

One discipline, two architectures. MOSA is a technical architecture (modular components behind open interfaces) and a business architecture (contracting, IP, data rights). A clean interface the Government cannot legally exploit is not, in MOSA terms, a success.

Core Frameworks & Mental Models

What MOSA is — and why it is mandatory

A Modular Open Systems Approach (MOSA) is a combined acquisition and design approach that pairs a technical architecture with a business architecture, both oriented around system interfaces that conform to widely supported, consensus-based standards. The structural payoff is severability: components can be added, removed, or swapped incrementally across the life cycle, opening the system to efficiency, competition, and innovation. MOSA is no longer discretionary — recent law compels it.

The statutory → regulatory → contract chain

Authority cascades, and a break anywhere (especially insufficient data rights) defeats the whole:

  • Statute — 10 U.S.C. 4401–4403 (4401 = mandate + definitions for MDAPs; 4402 = capabilities development and weapon-system design; 4403 = interface availability/support). The FY2017 NDAA introduced major system component and major system interface and required MOSA for MDAPs at Milestone A/B after Jan 1 2019; the FY2021 NDAA Section 804 added modular system interface, emphasized interface data and repositories, and expanded the mandate to all programs to the maximum extent practicable.
  • Regulation — the DFARS (Part 207.106, 227.7203-2; clauses 252.227-7013/-7015/-7018; rulemaking case 2021-D005) and the data-rights framework of DFARS 252.227.
  • Contract — the RFP, Acquisition Strategy, SEP, and CDD turn the mandate into a binding obligation on industry.

The five OUSD(R&E) pillars

The current authority's organizing framework (it supersedes the 2013 OSA guidebook), read as a progression where each pillar depends on the earlier ones:

  1. Establish an Enabling Environment — set requirements, business practices, strategy, and T&E methods before design hardens.
  2. Employ a Modular Design — identify each component's functionality before the RFP, so business and technical objectives drive the partitioning.
  3. Designate Modular Interfaces — decouple the interface from the implementation so a component and its interface can follow separate life cycles.
  4. Leverage Consensus-Based Open Standards — standardize interfaces with open, consensus-developed standards; manage Government-owned interface repositories.
  5. Certify Conformance — verify and validate that the implementation actually conforms to the selected open standards. Without this, the other four are claims, not facts.

The interface lifecycle (Figure 3-1)

A maintained, living framework: plan → modularize → identify interfaces → define interfaces → standardize interfaces. Plan measurable objectives and governance; decompose capability into self-contained functional modules; locate the boundaries where modules exchange data, signals, or commands; turn them into explicit protocols and data formats on open standards; lock the specifications to consistent open standards. It is a pipeline, not a menu — skip define or standardize and the modules aren't actually swappable.

Technical levers (§3.2)

  • WBS as MOSA taxonomy (MIL-STD-881F, MIL-STD-196G naming) — align the Work Breakdown Structure to MOSA principles (modularity, openness, scalability, flexibility, reusability), then call out modules, interfaces, and test needs (Table 3-1).
  • Standards selection and profiling — favor consensus-based standards (10 U.S.C. 4401), search ASSIST/MOSS, and write a profile to pin a standard's optional variability so implementations actually interoperate.
  • Software — design API-first with hardware-grade modular rigor; declare data rights at the right abstraction (DoDI 5000.87); for cybersecurity, prefer a DevSecOps + MBSE + consensus-standard (FACE/OMS) path over a single proprietary transport service.
  • COTS — run a business case analysis first; a design change to a COTS baseline can trigger costly regression testing or recertification, erasing the benefit.

Assessment, technology change, and roadmaps

  • Five benefit classes anchor metrics: Interoperability, Technology Refresh, Enhanced Competition, Innovation, Cost Avoidance/Savings — reduced to the necessary few per use case and maturity. Use pass/fail for a proposed architecture, metrics-based assessment (Appendix A) when supporting mechanisms exist.
  • DMSMS (obsolescence) is mitigated by multi-vendor sourcing through open interfaces and by involving DMSMS practitioners early; coordinate with USD(A&S).
  • Two roadmaps, one clock — a product roadmap (what value, when) plus a technology roadmap (what must be ready, when) isolate volatile technology behind stable interfaces.

Contracting and the implementation toolkit (Appendices)

  • Assessment tools chosen by stakeholder and level: PART (Army), OAAT/OAAM (Navy, business + technical axes 0–4), KOSS (NAVAIR, lock-prone subsystems), SEAM (Air Force). MAUT scores trade-offs against life-cycle cost.
  • Enforceability rides on deliverable data — CDRLs backed by DIDs (OSMP, SEMP, DSM) traced to WBS/GRA node levels; the DSM is constrained so it cannot alter Government-designated interfaces. Front-load: evaluate a draft OSMP before award. Non-FAR vehicles (OTAs) carry no DFARS data rights automatically while the MOSA mandate still applies.
  • Desired modularity is a deliberate cost-benefit point on a spectrum, and Conway's Law warns that the architecture inherits the organization's communication seams.

Chapter Index

#SectionKey content
ch01Introduction & PolicyMOSA definition; statutory chain (10 U.S.C. 4401–4403, FY2017/FY2021 NDAA); DFARS policy and clauses; data rights; terminology discipline
ch02Pillars & BenefitsThe five OUSD(R&E) pillars; primary benefits; secondary benefits; tri-Service memorandum; supersedes 2013 OSA
ch03Program Management & Interface LifecycleCost-benefit gate; plan→modularize→identify→define→standardize; JCIDS integration; mandatory + supporting documents; ICD/IRS
ch04Technical ConsiderationsWBS/MIL-STD-881F taxonomy; requirements; standards selection and profiling; API-first software; cybersecurity; COTS
ch05Assessment, Technology Change & RoadmapsFive benefit classes; pass/fail vs. metrics; DMSMS; product + technology roadmaps; Appendix A methodology
ch06Acquisition Pathways & ConclusionAAF and the six pathways; MCA prescriptiveness; EMD/P&D RFPs; MOSWG/TSWG governance
ch07Implementation AppendicesAssessment tools (PART/OAAT/KOSS/SEAM); GRA; contracting, CDRLs/DIDs; pillar actions; MAUT; workforce/DAU CLE 019

Topic Index

  • 10 U.S.C. 4401–4403 / statute → ch01, ch06
  • AAF (Adaptive Acquisition Framework) → ch06
  • Acquisition pathways (six) → ch06
  • Acquisition Strategy → ch03, ch06
  • API-first / software design → ch04
  • ASSIST / MOSS database → ch04
  • Assessment metrics / benefit classes → ch05
  • Assessment tools (PART, OAAT, KOSS, SEAM) → ch07
  • Benefits of MOSA → ch02
  • Business case analysis (COTS) → ch04, ch07
  • Conformance certification → ch02, ch07
  • Contracting / CDRLs / DIDs → ch07
  • Conway's Law → ch07
  • COTS → ch04, ch07
  • Cost-benefit analysis → ch03
  • Cybersecurity (software / hardware) → ch04
  • Data rights → ch01, ch07
  • Desired modularity → ch07
  • DFARS → ch01
  • DMSMS / obsolescence → ch05
  • Government Reference Architecture (GRA) → ch07
  • Interface lifecycle (plan/modularize/identify/define/standardize) → ch03
  • JCIDS → ch03
  • MAUT → ch07
  • MIL-STD-881F / WBS taxonomy → ch04
  • MOSWG / TSWG governance → ch06
  • NDAA (FY2017 / FY2021 Section 804) → ch01
  • Pillars (five OUSD(R&E)) → ch02, ch07
  • Profile (standards variability) → ch04
  • Roadmaps (product / technology) → ch05
  • SEP (Systems Engineering Plan) → ch03
  • Standards (consensus-based open) → ch04, ch02
  • Technology refresh / insertion → ch05
  • WBS → ch04

Supporting Files

  • glossary.md — key MOSA terms (statutory, pillar, interface, assessment, contracting), alphabetical, with chapter references
  • patterns.md — reusable patterns (cost-benefit gate, interface-lifecycle pipeline, WBS taxonomy, build-in-not-bolt-on, IP-rights targeting, contractual enforceability, metrics + roadmaps) with When/How/Trade-offs
  • cheatsheet.md — quick decision rules, the five pillars, benefit classes, the statute→regulation→contract chain, MOSA across the six pathways, mandatory vs. supporting documents, tells & smells

Scope & Limits

Covers: the Modular Open Systems Approach as U.S. DoD weapon-system acquisition and design policy per the OUSD(R&E) Implementing a MOSA in DoD Programs guidebook (Feb 2025) — the statutory and DFARS basis, the five pillars, the interface lifecycle, the technical levers (WBS taxonomy, standards profiling, software/cybersecurity, COTS), MOSA assessment metrics and service tools, technology-change/DMSMS management and roadmaps, MOSA across the AAF pathways, and the contracting/IP/data-rights mechanics and workforce considerations in the appendices.

Does not cover / thin on: the engineering of any specific interface standard — it names FACE, OMS, DISR, FIPS 140-2, etc. without reproducing or detailing them; the underlying systems-engineering processes that MOSA requirements ride on (use dau-se-guidebook / nasa-npr-7123) and general SE theory or open-architecture concepts beyond DoD policy (use sebok / se-standards-signpost); non-DoD or commercial open-systems practice; and the full text of the cited statutes, DFARS clauses, and 5000-series instructions (named, not reproduced). Terminology note: legacy terms such as key interface lack a current statutory definition and the appendices carry an older legacy five-pillar set alongside the current OUSD(R&E) pillars — anchor any non-statutory term to the statute.

Jurisdiction & source: U.S. Government public-domain work (Distribution A); guidance is mandatory for the DoD programs it governs and is current as of the February 2025 guidebook (DOPSR case 25-T-1210). Tracks an evolving statutory/regulatory landscape (e.g. renumbering of 10 U.S.C. 2320→3771, 2446a→4401; DFARS case 2021-D005 still finalizing) — verify citations against the current instruments.

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 Dod Mosa AI skill do?

Knowledge base from the OUSD(R&E) guidebook Implementing a MOSA in DoD Programs (Feb 2025). Use for the Modular Open Systems Approach as a DoD acquisition + design discipline: the statutory/regulatory basis (10 U.S.C. 4401–4403, FY2017/FY2021 NDAA, DFARS), the five OUSD(R&E) pillars, the plan→modularize→identify→define→standardize interface lifecycle, technical levers (WBS/MIL-STD-881F taxonomy, standards profiling, API-first software, COTS/cybersecurity), MOSA assessment metrics and tools (PART/OAAT/KOSS/SEAM/MAUT), technology-change and DMSMS management, roadmaps, MOSA across the six AAF...

Why use Dod Mosa on TypingMind?

Because you install it once and use it with any model. Dod Mosa 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 Dod Mosa in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jgsystemsconsulting/jgs-se-knowledge-packs/tree/main/packs/dod-mosa. 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 Dod Mosa?

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 Dod Mosa?

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

Is the Dod Mosa 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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