Cue — AI Operating System for Cursor

A portable control-plane for Cursor: specialized agents, enforced engineering gates, shared standards, and hub-resident project state (docs/projects/) so app repos stay thin. Languages: React (default), Python, Angular, plus Cue for hub/meta work and DaC for diagrams-as-code.

Canonical path rules: docs/_ai_system/standards/control-plane-paths.md

Recent Changes

Date	Change	Scope
2026-04-13	MCP hard-stop policy: `sequentialthinking` failures now abort with a visible error instead of silently falling back to inline reasoning. Supervisor runs a pre-dispatch health probe before spawning engineering subagents.	`.cursorrules`, `cue-supervisor.mdc`, `cue-engineering.mdc`
2026-04-13	MCP config fix: Resolved `spawn npx ENOENT` and `env: node: No such file or directory` for NVM-managed Node by using absolute paths and explicit `PATH` in `~/.cursor/mcp.json`.	`~/.cursor/mcp.json` (user-level)
2026-04-08	React rule gaps and review enforcement symmetry closed.	`.cursorrules`, agents, standards
2026-04-06	Dependency mapper integration with architectural boundary enforcement via `depmap-toolkit`.	Skills, standards, engineering workflow
2026-04-04	Excalidraw DaC agent track with routing, protocol, and style standard.	Agents, routing table, standards
2026-04-02	Orchestrator runs in main chat (not as subagent) for reliable Task spawning.	`.cursorrules`, `cue-supervisor.mdc`, `agent-orchestrator.md`

Orchestration Flow (How `/o` Works)

The /o (alias /orchestrate) shortcut runs the full engineering pipeline. The Orchestrator runs in the main chat (not as a subagent) and spawns each phase as a direct Task subagent. This eliminates unreliable nested Task spawning.

You: /o "Create user dashboard"
  |
  v
SUPERVISOR (main chat)
  |  detects /o
  |  resolves envelope (repo, branch, project, language, plan)
  |  loads Orchestrator rules (agent-orchestrator.md)
  |
  v
ORCHESTRATOR (main chat — takes over)
  |
  |  Phase 1: Spec
  |  +---> Task(generalPurpose) --> reads spec-{lang}.md --> creates plan
  |  <--- structured result
  |
  |  FOR EACH MILESTONE M[i]:
  |  |
  |  |  Phase 2: Code(M[i])
  |  |  +---> Task(generalPurpose) --> reads code-{lang}.md --> implements
  |  |  <--- structured result
  |  |
  |  |  Phase 3: Review(M[i])
  |  |  +---> Task(generalPurpose) --> reads review-{lang}.md --> 5-pass audit
  |  |  <--- structured result
  |  |       |
  |  |       +-- REJECT? --> Remediation loop (max 3 cycles) --> re-Review
  |  |
  |  |  Phase 4: QA L1(M[i])  [skip for CUE]
  |  |  +---> Task(generalPurpose) --> reads qa-{lang}.md --> baseline checks
  |  |  <--- structured result
  |  |
  |  |  Phase 5: QA L2(M[i])  [skip for CUE]
  |  |  +---> Task(generalPurpose) --> reads qa-resilience-{lang}.md
  |  |  <--- structured result
  |  |
  |  |  milestone_commit() --> save context to memory
  |  |  milestone_lookup() --> load context for M[i+1]
  |  |
  |  NEXT MILESTONE (carry deferred items forward)
  |
  v
COMPLETE (all milestones done, all deferred items resolved)

Auto-Chain Rules

Default: Phases and milestones chain automatically with no user interaction
--pause: The only way to stop between phases for user inspection (must be explicitly passed)
Circuit breaker: 3 consecutive failures on the same milestone stops the loop
Blocking error: Missing dependencies, plan not found, etc. stops the chain

Output Constraints (Per Phase)

Phase	May Edit	May NOT Edit
Spec	Plan files at `docs/projects/{PROJECT}/plans/active/`	Agent files, standards, profiles, rules, source code
Code	Source files, agent files, standards, profiles, rules per plan	Plan structure (marking tasks done is OK)
Review	Review report; Verification Contract Result column	Source files, agent files, standards
QA	QA result output only	Any files

What Cue Does

Cue gives Cursor a structured engineering process. Instead of a single AI that tries to do everything in one shot, Cue routes your request through specialized agents — each with strict protocols, mandatory reasoning gates, and quality checks — then hands off between phases using structured payloads.

  +-------+     +-----------+     +-------------+     +-----------+
  |  You  | --> | Supervisor| --> | Orchestrator| --> | Subagents |
  +-------+     +-----------+     | (main chat) |     | (Tasks)   |
                   |              +-------------+     +-----------+
                   |                 |                   |
                   |  /o (R/P/A)    +-> Spec --> Code --> Review --> QA
                   |                                      |
                   +-- /spec, /code  --> Direct Agent      |
                   +-- /docs, /jira  --> Ops Agent         |
                   +-- /dac ...      --> DaC Agent         |
                   +-- /test, /sec   --> Test/Sec Agent    |

System Architecture — Hub Control Plane

Cue's hub repo is the control plane for AI-assisted engineering: routing, agent protocols, standards, registry, vault layout, and canonical project artifacts under docs/projects/{project}/.

+----------------------------------------------------------+
|  CUE HUB — Control Plane                                 |
|                                                          |
|  .cursorrules + .cursor/rules/*.mdc   Supervisor & gates |
|  docs/_ai_system/agents/              Protocols          |
|  .cursor/agents/*.md                  Task subagents     |
|  docs/_ai_system/standards/           Standards          |
|  docs/projects/{project}/             Plans, knowledge   |
|  .cursor/skills/ + registry/          Toolkits           |
|  docs/architecture/                   DaC                |
|  lib/cue_vault/ + scripts/            Vault library      |
+----------------------------------------------------------+
          |
          | multi-root workspace
          v
+----------------------------------------------------------+
|  APP REPO — Minimal Spoke                                |
|                                                          |
|  .cue/version.json          --> hub root                 |
|  .cursor/rules/project-profile.mdc                       |
|  docs/_ai_system/standards/project-profile.md            |
|  .cue/vault/ (optional)                                  |
|  .jira/ (optional)                                       |
+----------------------------------------------------------+

Hub vs Spoke

The app repo is not a second home for Cue. Nothing from the hub is copied into the spoke for day-to-day work. Cursor loads the hub folder from the multi-root workspace; agents resolve paths on the hub per control-plane-paths.md.

Spoke (app repo)	Hub (this repo)
`.cue/version.json` → hub root	Agents, `.cursorrules`, `.cursor/rules`, `.cursor/agents`, standards, toolkits, registry
`.cursor/rules/project-profile.mdc`	`docs/projects/{project}/` — plans, knowledge, rules, profile
`docs/_ai_system/standards/project-profile.md`	Hub-shared knowledge: `docs/_ai_system/knowledge/`
Optional `.cue/vault/`, `.jira/`	Hub vault tiers, hub meta plans

How Cue Leverages Cursor

  Cursor Built-in Feature         How Cue Uses It
  ========================        ==============================
  Plan Mode                  -->  Architectural thinking phase
                                  (output feeds into /spec)

  .cursor/rules/*.mdc        -->  Targeted behavioral rules
                                  (load per glob pattern)

  .cursor/agents/*.md         -->  Orchestrator + phase subagents
                                  (spec, code, review, qa)

  MCP Servers                 -->  sequential-thinking MCP
                                  (mandatory reasoning gate)

  .cursor/skills/             -->  Service toolkits + MCP tools
                                  (External CRM, ML platform, DaC, memory, ...)

Plan Mode Integration

Cursor's built-in Plan Mode is Cue's thinking phase. Switch to Plan Mode for open-ended design discussion. When the design is ready, switch to Agent Mode and run /spec to formalize:

Plan Mode (design exploration) --> /spec (plan) --> /code --> /review --> QA

Glob-Activated Rules (.mdc)

Instead of loading every rule on every request, Cue uses Cursor's .mdc file format with glob-based activation:

Rule File	Activates On	What It Does
`cue-supervisor.mdc`	Always	Thin router — shortcuts, language detection
`cue-engineering.mdc`	Always	Scope analysis, decomposition, build gates
`cue-vault-intake.mdc`	Always	Credential intake protocol
`cue-author.mdc`	Always	Cue system authoring agent
`cue-react-coding.mdc`	`*/.tsx, */.jsx`	React state management, file thresholds
`cue-react-performance.mdc`	`*/.tsx, */.jsx`	Render optimization, memory safety
`cue-python-coding.mdc`	`*/.py`	Type hints, FastAPI, pytest
`cue-python-performance.mdc`	`*/.py`	Profiling, async, memory hot paths
`cue-angular-coding.mdc`	`*/.component.ts`	Angular patterns, change detection
`cue-angular-performance.mdc`	`*/.component.ts`	OnPush, lazy loading, bundle size
`cue-design-principles.mdc`	`*/.tsx, */.css`	Portal architecture, no modals
`cue-ux-behavior.mdc`	`*/.tsx`	Empty states, progressive disclosure
`cue-module-architecture.mdc`	`*/.tsx`	Component registry, design-system layout
`cue-no-standalone-scripts.mdc`	`scripts/test_*.py`	Deprecation guard — use toolkit MCP tools

MCP: Mandatory Structured Reasoning (Hard Stop on Failure)

Cue requires the sequential-thinking MCP server, auto-configured during /install. Every agent activation begins with a structured reasoning call before any output — no complexity threshold, no self-exemption.

Hard Stop Policy: If the MCP server is unavailable, agents must abort and surface the error to the user. Silent fallback to inline reasoning is explicitly forbidden. The Supervisor also runs a pre-dispatch health probe before spawning any /spec, /code, /review, or /sec subagent — catching MCP failures before work begins.

Full Engineering Lifecycle

  Plan Mode           /spec             /code             /review
  (optional)          (Architect)       (Builder)         (Auditor)
  +---------+     +------------+    +------------+    +------------+
  | Design  | --> | Create     | -> | Test-first | -> | 5-pass     |
  | explore |     | plan,      |    | increments,|    | audit:     |
  |         |     | complexity,|    | build      |    | arch, UX,  |
  +---------+     | milestones |    | verify     |    | spec-test, |
                  +------------+    +------------+    | trace, obs |
                                                      +------------+
                                                           |
                                              +------------+------------+
                                              v                         v
                                        +----------+            +------------+
                                        | QA L1    |            | Security   |
                                        | baseline |            | SAST/SCA   |
                                        +----------+            +------------+
                                              |
                                              v
                                        +----------+
                                        | QA L2    |
                                        | resilien.|
                                        +----------+

Context Isolation

Each phase runs in its own Task subagent (or its own chat session in manual mode). Handoffs are thin pointers to the plan — the Verification Contract in the plan is the source of truth for evidence.

App work plans live on the hub: <hubRoot>/docs/projects/{project}/plans/active/

Manual vs Orchestrated

Mode	Commands	What Happens
Manual	`/spec` -> `/code` -> `/review` -> `/sec` (separate chats)	You control each phase transition
Orchestrated	`/o "Create user dashboard"`	Auto-chains Spec -> Code -> Review -> QA L1 -> QA L2

Manual mode:

Step	Command	When
0	Switch to Plan Mode	Larger features needing design exploration
1	`/spec "Create user dashboard"`	Starting any new feature
2	`/code user-dashboard`	After Spec completes and plan exists
3	`/review user-dashboard`	After Code completes with build proof
4	`/sec user-dashboard`	Before deploy (security gate)

`/o` Flags

Flag	Effect
`--pause`	Stop between phases for user inspection
`--python` / `--angular` / `--cue`	Set language context
`--project [name]`	Target a specific project
`--spec` / `--code` / `--review`	Start at a specific phase

Memory Bridge

The Orchestrator uses a SQLite-based memory system (.cue/memory/memory.db) to bridge context across milestone boundaries:

Tool	Purpose
`milestone_commit`	Save handoff context after each phase
`milestone_lookup`	Load prior context before milestone N+1
`troubleshoot_search`	Recall past fixes when circuit breaker fires
`troubleshoot_commit`	Record new debugging knowledge

Supervisor Routing

Every request passes through the Supervisor — a thin router that detects intent, resolves language, and delegates to the matched agent.

  User Request
       |
       v
  Shortcut Scan (/spec, /o, /dac, /install, ...)
       |
       v
  Language + Flags (--python, --react, --angular, --cue, --project)
       |
       v
  Project Detection --> docs/projects/{name}/
       |
       v
  MCP Health Probe (for /spec, /code, /review, /sec — hard stop if down)
       |
       v
  Classify Category (UI, Backend, Docs, Ops, DaC)
       |
       +---> Engineering (R/P/A) --> Orchestrator (main chat) --> Task subagents
       +---> DaC track            --> /dac spec|code|review|deploy
       +---> Documentation        --> /docs-user, /docs-dev, /roadmap
       +---> Operations           --> /install, /jira, /check, /feedback
       +---> Cue meta             --> /cue-author, --cue agents
       +---> Testing/Security     --> /test, /sec

Every request echoes a Supervisor Decision block so you can verify routing:

SUPERVISOR DECISION:
Project: example-backend
Branch: feature/api-layer
Language: PYTHON
Category: Backend/Service
Via: Orchestrator
Agent: docs/_ai_system/agents/agent-orchestrator.md
Rules Consulted: .cursorrules, cue-supervisor.mdc, project-profile.md

Task Decomposition

Cue prevents "vibe coding" through complexity-driven rigor. The Spec Agent scores every feature on a 0-6 scale, and that score controls how much structure is enforced.

  Feature Request
       |
       v
  Complexity Score (0-6)
  Files x State x Dependencies x Reversibility x Impact
       |
       +-- 0-1 --> Single Task (streamlined plan, Pass 1 review only)
       |
       +-- 2-3 --> Task List (full plan, dependency ordering, all review passes)
       |
       +-- 4-5 --> Milestones + Increments (bailout plan, milestone-per-chat)
       |
       +-- 6   --> Phased Delivery (scope must be reduced or split)

Milestone and Increment Model (Complexity 3+)

  Feature
  +-- Milestone 1: "User can upload a file" (200-600 lines)
  |   +-- Increment 1.1: Define types            (~30 lines)
  |   +-- Increment 1.2: validateFile()           (~50 lines)
  |   +-- Increment 1.3: useFileUpload hook        (~80 lines)
  |   +-- Increment 1.4: FileDropZone UI           (~100 lines)
  |   +-- Increment 1.5: Wire up + E2E verify
  |
  +-- Milestone 2: "Upload shows progress"
  |   +-- (increments...)
  |
  +-- Milestone 3: "Upload handles errors"
      +-- (increments...)

The Increment Execution Loop

READ input --> WRITE test --> IMPLEMENT (~30-100 lines) --> VERIFY output
--> VERIFY integration --> SIZE CHECK --> LOG completion --> ADVANCE

If the same approach fails twice, the retry circuit breaker fires — the agent must stop and invoke structured reasoning before the third attempt.

Structured Reasoning (MCP)

Every Spec, Code, Review, and Security agent activation must begin with a sequentialthinking MCP call before producing any output.

  You: /code my-feature --python
       |
  Supervisor: loads Orchestrator rules
       |
  Orchestrator: spawns Code subagent via Task
       |
  Code Subagent:
       +---> sequentialthinking MCP (mandatory gate)
       |     decompose, identify risks, produce sequence
       |
       +---> Implement + build verify
       |
       +---> Return structured result to Orchestrator

If the MCP server is unavailable, agents hard stop and surface the error — silent fallback is forbidden. The server is auto-configured during /install.

Agents

Engineering Agents (Polyglot)

Agent	Role	React	Python	Angular	Cue
Spec	Architect	`agent-spec.md`	`agent-spec-python.md`	`agent-spec-angular.md`	`agent-spec-cue.md`
Code	Builder	`agent-coding.md`	`agent-coding-python.md`	`agent-coding-angular.md`	`agent-coding-cue.md`
Review	Auditor	`agent-review.md`	`agent-review-python.md`	`agent-review-angular.md`	`agent-review-cue.md`
Orchestrator	Lifecycle	Runs in main chat for all languages
DaC	Diagrams	—	—	—	`agent-spec-dac.md` ...

QA Agents (Orchestrator-dispatched)

Agent	Layer	React	Python	Angular
QA L1	Global baseline	`qa-react.md`	`qa-python.md`	`qa-angular.md`
QA L2	Resilience	`qa-resilience-react.md`	`qa-resilience-python.md`	`qa-resilience-angular.md`

QA agents are auto-dispatched by the Orchestrator after Review passes. L1 checks global baselines. L2 focuses on operational durability. Both skip for CUE language.

Security, Testing, Documentation, Operations

Agent	Shortcut	Role
Security	`/sec`	SAST/SCA gate
Test	`/test`	API explore / pytest probes
User Guide	`/docs-user`	Technical writing
Dev Doc	`/docs-dev`	Architecture docs
Roadmap	`/roadmap`	Changelog and releases
Install	`/install`	Project onboarding
Update	`/update`	Bump hub pointer
Jira	`/jira`	Issue tracking
Feedback	`/feedback`	System evolution
Cue Author	`/cue-author`	Author agents, rules, registry

Language flags: --python, --react, --angular, --cue, --dac (or auto-detected from keywords and project profile).

Service Toolkits

Cue follows a Toolkit-First pattern for external service integrations. All service interactions go through registered MCP tools that resolve credentials via the vault chain.

  Agent --> check skills.yaml --> Toolkit SKILL.md --> MCP Tool --> Vault Chain
                                                          |
                                                   structured response

Registered Toolkits

Toolkit	Service	Capabilities
`crm-toolkit`	ExternalCRM	Knowledge article CRUD, case query, notes
`ml-toolkit`	ML platform	Ingest, retrieve, list, prompts
`content-platform-toolkit`	ContentPlatform	Article CRUD, LiQL search, tags, images
`prompt-store-toolkit`	PromptStore	Prompt push/pull/list
`cue-example-app-feedback`	example-app	Feedback comparison, section diff
`cue-example-app-e2e`	example-app	E2E read/create pipeline
`dac-toolkit`	DaC (local)	Parse/validate DSL, upsert containers/components
`dac-discovery-toolkit`	DaC (local)	Scan services, APIs, dependencies
`structurizr-toolkit`	Structurizr	Push workspace, render DSL
`browser-verify`	Local	Playwright-style browser verification
`memory-toolkit`	Local (SQLite)	Milestone handoffs, troubleshooting recall

Core MCP Tools

Tool	Purpose
`vault_resolve`	Credential resolution from vault chain
`build_verify`	Run type checker, linter, tests, dev server
`health_check`	Service connectivity verification
`cue_system_check`	Hub/spoke structure, registry, MCP, vault sanity

Review Agent: 5-Pass Audit

Pass	Focus	Blocks Merge
1A	Code architecture, state management, file size thresholds	Yes
1B	Structural integrity (milestone state machine, I/O contracts)	Yes (complexity 3+)
2	UX behavior scorecard (empty states, help panels, tooltips)	Yes
3	Spec-test alignment, cross-task regression	Yes
4	Cue trace verification (correct agent, correct rules)	Yes
5	Observable verification (browser, logs, behavior)	Yes (complexity 2+)

File Size Enforcement

Tier	Action
Target	Ideal range — no action
WARN	Evaluate extraction points
REJECT	Must decompose before proceeding
HARD STOP	Unconditional reject — must split

React Component (.tsx): Target 150-200, WARN 300, REJECT 500, HARD STOP 800

Global Flags

Flag	Effect
`--trace`	Waterfall debug logging with section-level tracking
`--pause`	Stop between phases for user inspection (orchestrated mode only)
`--no-standards`	Skip standards loading
`--no-jira`	Skip auto Jira payload generation
`--project [name]`	Set active project
`--python` / `--react` / `--angular` / `--cue` / `--dac`	Set language context

Shared Config Vault

Per-project credential management with tiered resolution (project -> hub -> shared), interactive installer, health checks, and .env sync.

Resolution Order (highest wins)

Environment variables (.env / shell)
Project vault (.cue/vault/credentials.yaml)
Hub project vault (cue/.cue/vault/{project}/)
Hub shared vault (cue/.cue/vault/shared/)
Global vault (~/.cue/vault/) — legacy fallback

Python Resolver

from cue_vault import FileVaultResolver

vault = FileVaultResolver()
token = vault.get_credential("external_crm.api_token")
model = vault.resolve_model("Claude Sonnet")
env   = vault.hydrate_env(["external_crm", "cx_playground"])

Interactive Setup

python scripts/init-vault.py --interactive    # Guided service picker
python scripts/init-vault.py --verify         # Health-check services
python scripts/init-vault.py --sync           # Re-sync .env from vault

Quick Start

1. Clone Cue

cd ~/your-workspace
git clone https://github.com/your-org/cue.git

2. Install into Your Project

/install my-project

3. Configure Your Project (on the hub)

Define or edit the project slice under docs/projects/{project}/ (profile, plans, knowledge) per control-plane-paths.md.

4. Set Up Vault (Python Projects)

pip install -e ../cue/lib/cue_vault
python ../cue/scripts/init-vault.py --interactive

5. Start Building

/spec "Create user dashboard"               # React (default)
/spec "Create auth service" --python         # Python
/spec "Create data grid" --angular           # Angular
/o "Full feature implementation"             # Orchestrated pipeline

Adding a New Language

Create 3 agent files: agent-spec-[lang].md, agent-coding-[lang].md, agent-review-[lang].md
Create 2 .mdc rules: cue-[lang]-coding.mdc, cue-[lang]-performance.mdc
Create 1 performance standard: performance-[lang].md
Update .cursorrules with --[lang] flag and detection signals
Register in rule_registry.md
Add to install-cue.ts file copy list

Repository Structure

cue/
+-- .cursorrules                  # Supervisor (polyglot router)
+-- .cursor/
|   +-- agents/                   # Task subagent prompts (spec, code, review, qa, orchestrate)
|   +-- rules/                    # Glob-activated .mdc rules
|   +-- mcp.json
|   +-- mcp-server/               # MCP server (core + toolkit discovery)
|   +-- skills/                   # Toolkits (External CRM, ML platform, DaC, Structurizr, example-app, ...)
+-- .cue/
|   +-- version.json
|   +-- vault/
|   +-- memory/memory.db          # Milestone + troubleshooting SQLite (FTS5 + embeddings)
|   +-- registry/skills.yaml
+-- docs/
|   +-- _ai_system/               # Agents, standards, registry, hub-shared knowledge
|   +-- projects/{project}/       # Control plane: per-project plans, knowledge, rules
|   +-- architecture/             # DaC: workspace.dsl, exports, decisions
|   +-- plans/active|archive/     # Hub-only (meta) plans
+-- lib/cue_vault/
+-- scripts/
+-- registry/services.yaml
+-- tests/

License

MIT

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
.cue		.cue
.cursor		.cursor
.jira/pending		.jira/pending
.storybook		.storybook
docs		docs
lib/cue_vault		lib/cue_vault
registry		registry
scripts		scripts
src		src
tests		tests
.cursorrules		.cursorrules
.gitignore		.gitignore
INSTALL.md		INSTALL.md
LICENSE		LICENSE
README.cue-subs.md		README.cue-subs.md
README.md		README.md
conftest.py		conftest.py
package.json		package.json
playwright.config.ts		playwright.config.ts
tsconfig.json		tsconfig.json
tsconfig.node.json		tsconfig.node.json
vite.config.ts		vite.config.ts

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Cue — AI Operating System for Cursor

Recent Changes

Orchestration Flow (How /o Works)

Auto-Chain Rules

Output Constraints (Per Phase)

What Cue Does

System Architecture — Hub Control Plane

Hub vs Spoke

How Cue Leverages Cursor

Plan Mode Integration

Glob-Activated Rules (.mdc)

MCP: Mandatory Structured Reasoning (Hard Stop on Failure)

Full Engineering Lifecycle

Context Isolation

Manual vs Orchestrated

/o Flags

Memory Bridge

Supervisor Routing

Task Decomposition

Milestone and Increment Model (Complexity 3+)

The Increment Execution Loop

Structured Reasoning (MCP)

Agents

Engineering Agents (Polyglot)

QA Agents (Orchestrator-dispatched)

Security, Testing, Documentation, Operations

Service Toolkits

Registered Toolkits

Core MCP Tools

Review Agent: 5-Pass Audit

File Size Enforcement

Global Flags

Shared Config Vault

Resolution Order (highest wins)

Python Resolver

Interactive Setup

Quick Start

1. Clone Cue

2. Install into Your Project

3. Configure Your Project (on the hub)

4. Set Up Vault (Python Projects)

5. Start Building

Adding a New Language

Repository Structure

License

About

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