Creativityliberty

nexus

Unified mission engine + AI-agent skill system. Intercepts any project request (SaaS, app, API, CLI, agent) and decomposes into Goal → Mission → Task → Flow with quality gates and deliverable artifacts. Also installs and generates llms.txt / SKILL.md for 39+ AI agents with agent-native optimization from 32 system prompt profiles. Trigger on: project ideas, "je veux faire", "build me", "create a", SaaS, MVP, app, platform, skill setup, llms.txt, SKILL.md, agent docs, or any complex task needing structured decomposition before execution.

Creativityliberty 0 Updated 2mo ago

Resources

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GitHub

Install

npx skillscat add creativityliberty/nexusskill

Install via the SkillsCat registry.

SKILL.md

NEXUS — Mission Engine + Agent Skill System

One system. Two modes. Every project, every agent.

 USER: "Je veux faire un SaaS de X"
                    ↓
 ╔═══════════════════════════════════════════╗
 ║              N E X U S                    ║
 ║                                           ║
 ║  MODE A: MISSION          MODE B: SKILLS  ║
 ║  ┌──────────────┐    ┌─────────────────┐  ║
 ║  │ INTERCEPT    │    │ DETECT stack    │  ║
 ║  │ DECOMPOSE    │    │ FETCH docs      │  ║
 ║  │ PLAN flows   │    │ GENERATE skills │  ║
 ║  │ EXECUTE+gate │    │ OPTIMIZE /agent │  ║
 ║  │ DELIVER arts │    │ INSTALL 39 dirs │  ║
 ║  └──────┬───────┘    └────────┬────────┘  ║
 ║         └─────────┬───────────┘           ║
 ║                   ▼                       ║
 ║         ARTIFACTS + SKILLS                ║
 ║    docs, code, specs, agent skills        ║
 ╚═══════════════════════════════════════════╝

Mode Selection

NEXUS auto-detects which mode to run:

User Says Mode What Happens
"Build me a SaaS..." MISSION Full decomposition → execution → artifacts
"Install skills for my project" SKILLS Detect deps → fetch → install for agents
"Generate llms.txt for my API" SKILLS Analyze docs → generate llms.txt + SKILL.md
"Create a platform with agent tools" BOTH Mission plan + agent skills installed

When in doubt, default to MISSION mode — it's more comprehensive and will
invoke SKILLS mode as a task within the mission when needed.


MODE A: MISSION ENGINE

A1. INTERCEPT — Capture Intent

Extract from user's message:

Field Extract Default if Missing
Vision What they want to build — (must be stated)
Domain Business/tech area "Web application"
Users Target audience "General users"
Core Value Key differentiator First feature mentioned
Constraints Stack, timeline, team Next.js + Supabase, 6 weeks, solo dev

Ask max 3 questions if critical info is missing. Otherwise, proceed with defaults.

A2. DECOMPOSE — Build Mission Hierarchy

GOAL (1)
  └─ MISSION (1-3 phases)
       └─ TASK (3-8 per mission)
            └─ SUB-TASK (2-5 per task)
                 └─ FLOW (steps + gate)

Goal definition:

goal:
  id: G-001
  title: "{Measurable goal}"
  success_criteria: ["{Metric 1}", "{Metric 2}", "{Metric 3}"]
  constraints:
    timeline: "{N weeks}"
    stack: "{Technologies}"
    team: "{Team size}"

Mission breakdown — each mission is a phase with a gate and artifacts:

missions:
  - id: M-001
    title: "Foundation & Architecture"
    gate: "Architecture validated, scaffold running"
    artifacts: [PRD, Architecture doc, Data model, Scaffold]
  - id: M-002
    title: "Core MVP"
    gate: "Core features working end-to-end"
    artifacts: [Auth, CRUD, UI, Database]
  - id: M-003
    title: "Polish & Launch"
    gate: "Deployed, tested, documented"
    artifacts: [Tests, Landing page, Deployment, Docs]

Task decomposition — each task has sub-tasks and an artifact:

tasks:
  - id: T-001
    mission: M-001
    title: "Define product requirements"
    artifact: "docs/prd.md"
    sub_tasks: ["User stories", "Data model", "User flows"]
    delegate_to: "prd-builder"  # if available

Flow patterns:

flows:
  dev:   [analyze, design, implement, test, review]
  arch:  [research, evaluate, decide, document, validate]
  deploy: [build, test, stage, verify, deploy]

Multi-flow — parallel execution for independent tasks:

multi_flow:
  - parallel: [T-005, T-006, T-007]  # Auth + CRUD + API in parallel
    sync_gate: "All integrated and tested"

A3. PLAN — Present Mission Briefing

Show the user the full plan before executing:

# Mission Briefing: {Goal}

## Phase 1: Foundation (Week 1-2)
Artifacts: 📄 PRD │ 📐 Architecture │ 📊 Data Model │ 🏗️ Scaffold
Tasks: T-001 → T-002 → T-003 → T-004
Gate: ✅ Architecture validated

## Phase 2: Core MVP (Week 3-4)
Artifacts: 🔐 Auth │ 📝 CRUD │ 🎨 UI │ 💾 Database
Tasks: T-005 ═╦═ T-006 ═╦═ T-007 → T-008
              ║ parallel ║
Gate: ✅ Core flow working end-to-end

## Phase 3: Launch (Week 5-6)
Artifacts: 💳 Payments │ 🧪 Tests │ 🌐 Landing │ 🚀 Deploy
Gate: ✅ Live and monitored

Wait for user approval or modifications before executing.

A4. EXECUTE — Run With Quality Gates

Execute each task, producing artifacts. At each gate:

GATE: {Name}
├─ ✅ Artifacts produced?
├─ ✅ Quality criteria met?
├─ ✅ Dependencies satisfied?
└─ ✅ User validated?
→ PASS / PARTIAL / FAIL

Execution rules:

  1. Every task produces a tangible artifact (file, not just text)
  2. Delegate to specialized skills when available (see integration map below)
  3. Show progress after each task
  4. At Phase 1 completion → auto-trigger MODE B to install agent skills

A5. DELIVER — Artifacts Catalog

Standard output structure:

docs/prd.md, architecture.md, data-model.md, user-stories.md, adr/
src/ (project code)
tests/ (test suite)
deploy/ (Dockerfile, CI/CD)
.agents/skills/ (agent skills — from Mode B)

Adaptive Complexity

Complexity Behavior
1-3 (Simple) Skip missions. Goal → 3-5 tasks → deliver
4-6 (Medium) 1-2 missions, sequential flow
7-10 (Complex) 3 missions, multi-flow, strict gates

MODE B: AGENT SKILL SYSTEM

B1. DETECT — Project Stack + Agents

Scan for dependency manifests: package.json, requirements.txt, Cargo.toml,
go.mod, Gemfile, composer.json, pubspec.yaml, build.gradle, *.csproj.

Scan for installed AI agents by checking home directories. See
references/agents-full-list.md for the complete 39-agent mapping.

B2. FETCH — Search & Download

Priority: llms.txt Hub registry → project /llms.txt → GitHub → generate from docs.

Use npx llmstxt-cli install <n> when available, or scripts/install_skills.sh.

B3. GENERATE — Produce llms.txt & SKILL.md

From project docs, generate:

  • llms.txt — concise index (llmstxt.org spec, see references/llmstxt-spec.md)
  • llms-full.txt — complete docs (<500KB)
  • SKILL.md — agent-ready with YAML frontmatter (description ≤1024 chars)

Use scripts/generate_llmstxt.py for automated generation.

B4. OPTIMIZE — Agent-Native Adaptation

Each agent reads skills differently. Adapt using profiles from
references/agent-native-profiles.md (derived from 32 system prompts):

Agent Style Max Lines Key Convention
Claude Code Reasoning + examples 500 YAML frontmatter, explain WHY
Cursor Dense imperative 200 Front-load patterns, code > prose
Windsurf Workflow steps 400 Numbered steps, cascade pattern
Cline/Roo Tool-use procedural 400 Tool call examples, decision trees
Copilot Example-heavy 300 Code patterns, signatures
Universal Clean markdown 400 No custom tags, portable

Use scripts/optimize_for_agent.py --agent {name} for per-agent optimization.

B5. INSTALL — Multi-Agent Distribution

.agents/skills/{name}/SKILL.md    ← canonical
.claude/skills/{name} → symlink
.cursor/skills/{name} → symlink
.windsurf/skills/{name} → symlink
... (39 agent directories)

Update config files: CLAUDE.md, .cursorrules, .windsurfrules.


Skill Integration Map

NEXUS orchestrates all available skills:

Need Delegate To Fallback
Full context context-builder Inline
PRD prd-builder context-builder
Architecture agent-architecture-builder Inline
Multi-agent numtema-universal-framework Inline
Workflows numflow-llm Inline
Next.js scaffold bun-nextjs-starter Manual
Agent skills llmstxt-skill-installer Mode B inline
Deep reasoning morphosys-cognitive-engine Standard
Prompts vortex-meta-prompt-engineer Inline
Documents docx, pptx, xlsx, pdf skills Markdown

Scripts

Script Purpose
scripts/install_skills.sh Standalone skill installer (no npm)
scripts/generate_llmstxt.py Generate llms.txt / SKILL.md from docs
scripts/optimize_for_agent.py Adapt SKILL.md per agent profile

Key Principles

  1. Plan before code — Mission briefing comes first, always
  2. Every task → artifact — No task completes without a tangible output
  3. Gates prevent drift — Validate before advancing to next phase
  4. Agent-native skills — Optimize for each agent's internal conventions
  5. Delegate to specialists — Use other skills when they exist
  6. Adapt to complexity — Simple idea? Light plan. Complex SaaS? Full hierarchy.
  7. User controls everything — The plan is a proposal, not a mandate