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agent-ops-stack

Manifest Schema Version CI Status Tests Composed Modules Python Versions Platforms Local-First Architecture Security Invariant Security SLA Third-Party Audited Marketing Log Code style: Ruff License Ecosystem Umbrella LLM-Ready

agent-ops-stack

🇩🇪 Deutsche Version

A manifest-driven composition of the local agent-ops ecosystem: the coordination layer that lets one or more AI coding agents (Claude Code, Codex, Gemini/Antigravity, Kimi, or any other CLI agent) collaborate effectively on the same machine without race conditions, know where to route tasks, make grounded decisions when the human operator is away, and align cross-device workflows safely.

This repository is composition and documentation, not monolithic source code: it lists seven focused, independently maintained modules in agent-ops.manifest.json and provides a thin installer (install.sh) that clones and reports their wiring. See ellmos-ai/stacks for the shared stack manifest schema specification and ecosystem catalog.

Machine-readable context for LLMs and agentic tools: llms.txt.

Note

AI Agent & LLM Context: This repository provides structured machine-readable context via llms.txt. Autonomous CLI agents (Claude Code, Codex, Gemini/Antigravity, Kimi) can parse this manifest-driven composition to understand local coordination, locking, ticket routing, user-decision avatars, and MCP server control planes.


Quick Navigation

  1. Overview & Architecture
  2. What is Agent-Ops?
  3. Target Personas & Discoverability
  4. Comparative Matrix vs. Alternatives
  5. Composed Modules (The 7 Pillars)
  6. System Architecture Flowchart
  7. Multi-Agent Operational Lifecycle Sequence
  8. Governance & Runtime Invariants
  9. How an Agent Uses This Stack
  10. Quickstart & Installation
  11. Manifest Schema Specification
  12. Sibling Ecosystem & Cross-Integration Matrix
  13. Search, SEO & Disambiguation
  14. Security Model & Threat Mitigation
  15. Third-Party Licenses & Transparency
  16. Verification & Automated Test Suite
  17. Security Policy & SLAs
  18. License & Liability / Haftung

1. Overview & Architecture

When multiple autonomous or interactive CLI coding agents operate simultaneously on a developer's machine, standard file systems lack native concurrency controls, shared task registries, and cross-session memory. agent-ops-stack packages the essential local operational tooling into a coherent, declarative stack:

Dimension Specification
Manifest Schema ellmos-stack-manifest-v1 (agent-ops.manifest.json)
Composed Pillars 7 specialized modules across coordination, sync, decisions, skills, and MCP
Network Footprint 100% Local-First & Zero Egress (zero external telemetry or remote tracking)
Privilege Model Unprivileged User-Mode (Non-Elevation; zero root/admin requirements)
Target Runtime Linux, macOS, and Microsoft Windows (cross-platform OS parity)
Agent Support Claude Code, OpenAI Codex, Google Antigravity / Gemini, Moonshot Kimi, custom CLI agents
your AI coding agent
├── MCP access (talks to these directly via stdio)
│   ├── controlcenter-mcp   → control-plane (consumes: skill-pack)
│   └── homebase-mcp        → mcp-runtime, memory-facade, task-facade (consumes: locking, ticket-routing)
└── file-/protocol-based conventions (agent reads & follows directly)
    ├── ticket-master           → ticket-routing
    ├── lock-master             → locking
    ├── sync-master             → file-sync
    ├── build-your-users-mind   → decision-avatar (consumes: interaction-logs)
    └── skills                  → skill-pack

2. What is Agent-Ops?

Any AI coding agent operating on the user's local system repeatedly encounters the same handful of questions before touching project files:

  • Is another agent or automation currently modifying this workspace?
  • Where should a discovered bug, change request, or subtask be recorded and routed?
  • What would the human operator decide when an ambiguous architectural trade-off arises while they are away?
  • What reusable skills, patterns, or workflows exist, and how should local MCP servers be bundled?
  • How are file updates coordinated across multiple devices without corrupting local Git states?

agent-ops-stack solves these challenges through seven focused, composable modules rather than a heavy monolithic framework. Each component is independently useful and versioned, yet harmonized through declarative wiring.


3. Target Personas & Discoverability

agent-ops-stack is purposefully engineered for four key stakeholder personas across autonomous engineering and enterprise toolchains:

  • [PERSONA-01] Autonomous AI Agent Framework & Multi-Agent Swarm Engineers: Engineers deploying multiple autonomous CLI coding agents (Claude Code, OpenAI Codex, Google Antigravity / Gemini, Moonshot Kimi) on shared local workspaces who require bulletproof, fail-closed file locking (lock-master) and structured ticket routing (ticket-master) to eliminate race conditions and conflicting write edits.
  • [PERSONA-02] Multi-Host & Edge Infrastructure Systems Engineers: Developers working interchangeably across multiple workstations, laptops, and remote servers who require slot-gated synchronization (sync-master) to coordinate project files safely without Git index corruption, split-brain merge collisions, or cloud storage lockouts.
  • [PERSONA-03] Solo Developers & Tool Builders: Individual programmers needing a lightweight, non-monolithic harness that manages ticket backlogs, captures task requirements, and provides an empirical decision avatar (build-your-users-mind) that answers ambiguous architectural questions when the human operator is away.
  • [PERSONA-04] Enterprise Tooling, Safety & Governance Compliance Officers: Compliance leaders mandating 100% offline, local-first operations with zero external network egress, unprivileged user-mode execution (RunAsInvoker), auditable third-party license inventories, and formal 48h vulnerability response SLAs.

High-Intent Search Queries & Discovery Keywords

Query Type English Intent Target German Intent Target
Primary Architectural local-first multi-agent coordination stack lokaler Multi-Agenten Koordinations-Stack
Concurrency & Locks CLI coding agent file locking and ticket routing Dateisperren und Ticket-Routing für KI Coding Agenten
Agent Interoperability Claude Code Codex Gemini Kimi local coordination lokale Koordination Claude Codex Antigravity Kimi
Control Plane & MCP MCP control plane for local AI agents MCP Steuerebene für lokale Entwickler-Agenten
Zero Egress & Safety offline zero-egress agent harness Zero-Egress Multi-Agenten Kollisionsschutz
Manifest Composition declarative agent ops manifest schema deklaratives Agent-Ops Manifest Schema

4. Comparative Matrix vs. Alternatives

The table below contrasts agent-ops-stack against four common industry alternatives across 10 core architectural and governance dimensions:

  1. Cloud SaaS Observability: Hosted monitoring and telemetry platforms (e.g. AgentOps.ai, LangSmith, Helicone).
  2. Monolithic Frameworks: Heavy multi-agent execution runtimes (e.g. AutoGen Studio, CrewAI Enterprise, LangGraph Cloud).
  3. Ad-Hoc Scripts & Worktrees: Manual Git worktrees, raw bash wrappers, and uncoordinated local shell scripts.
  4. Traditional Message Brokers: Heavy server daemons (e.g. RabbitMQ, Redis Pub/Sub, Celery).
Dimension & Invariant agent-ops-stack Cloud SaaS Observability Monolithic Frameworks Ad-Hoc Scripts / Worktrees Traditional Brokers
1. 100% Local-First & Zero Egress (INV-LOCAL-01) Yes (Strictly Local) No (Cloud Egress Required) Partial (Often Phone-Home) Yes (Local Only) Partial (Network Port Needed)
2. Unprivileged User-Mode (INV-USER-02) Yes (RunAsInvoker) Yes (User-Level API) Often Needs Daemon / Docker Yes (Standard User) No (Daemon / Root Ports)
3. Fail-Closed File Lock Integrity (INV-LOCK-03) Yes (lock-master) No (Observability Only) Proprietary In-Memory No (Blind Git Overwrites) No (Requires External Broker)
4. Structured Ticket & Bug Routing (INV-ROUT-04) Yes (ticket-master) No (Telemetry Traces Only) Ad-Hoc Task Memory No (Untracked Modifs) Message Passing Only
5. Decision-Avatar Theory-of-Mind (INV-AVAT-05) Yes (build-your-users-mind) No (Telemetry Only) No (Stateless System Prompts) No (Manual Human Input) No (Payload Agnostic)
6. Declarative Manifest Blueprint (INV-MANI-06) Yes (ellmos-stack-manifest-v1) Proprietary Cloud Schema Complex Python DSL Config None (Hardcoded Paths) Complex Broker Config
7. Immutable Release-Tag Pinning (INV-PIN-07) Yes (Release Tags) SaaS Controlled Updates Fast-Moving Package Drift No (Unversioned Scripts) Package Manager Driven
8. Sandboxed Installer Boundary (INV-SAND-08) Yes (Isolated ./modules/) Remote Agent Binaries System-Wide pip / npm Bloat Ad-Hoc Repository Sprawl System Service Daemons
9. Cross-Device Slot-Gated Sync (INV-SYNC-09) Yes (sync-master) Cloud Vendor Lock-In Single-Host Only High Merge / Cloud Race Risk Cluster Infrastructure Required
10. 48h Security & Triage SLA (INV-SLA-10) Yes (Formal 48h/5d SLA) Standard SaaS Terms Best-Effort Community No SLA / Unmaintained Upstream Vendor SLAs

5. Composed Modules (The 7 Pillars)

Module Role Provides Consumes Repository
ticket-master Cross-platform, multi-provider workflow engine: captures problem descriptions, scores priority, and routes tickets to appropriate projects or delegates ticket-routing dev-bricks/ticket-master
lock-master Zero-dependency, config-driven file lock system (LOCK*.txt): signals active project usage to prevent concurrent editing collisions locking dev-bricks/lock-master
sync-master Serverless file-sync coordination: slot rules and gated daily sync rituals across multi-machine setups file-sync dev-bricks/sync-master
build-your-users-mind Empirical user decision-avatar: constructs a theory-of-mind model from interaction history to guide autonomous decisions in operator absence decision-avatar interaction-logs ellmos-ai/build-your-users-mind
skills Portable AI skill library in Anthropic SKILL.md format: standalone process skills, developer workflows, and utility toolchains skill-pack ellmos-ai/skills
controlcenter-mcp MCP control plane: discovers local MCP servers, reads profile files, resolves capability bundles, and recommends task-specific tool configurations control-plane skill-pack ellmos-ai/ellmos-controlcenter-mcp
homebase-mcp Local-first MCP server for shared memory, knowledge, routing, swarm patterns, and task facade over canonical local stores mcp-runtime, memory-facade, task-facade locking, ticket-routing ellmos-ai/ellmos-homebase-mcp

6. System Architecture Flowchart

The following interactive Mermaid flowchart illustrates how the seven modules organize into functional operational layers around the active coding agents:

flowchart TD
  subgraph AGENTS ["Active Coding Agents"]
    A1["Claude Code"]
    A2["Codex"]
    A3["Gemini / Antigravity"]
    A4["Kimi / CLI Agent"]
  end

  subgraph COORDINATION ["Coordination & Locks"]
    TM["dev-bricks/ticket-master\n(ticket-routing)"]
    LM["dev-bricks/lock-master\n(locking)"]
  end

  subgraph DECISION ["Decision & Memory Layer"]
    BYUM["ellmos-ai/build-your-users-mind\n(decision-avatar)"]
    SK["ellmos-ai/skills\n(skill-pack)"]
  end

  subgraph MCP ["MCP Control Plane & Runtime"]
    CC["ellmos-ai/ellmos-controlcenter-mcp\n(control-plane)"]
    HB["ellmos-ai/ellmos-homebase-mcp\n(mcp-runtime)"]
  end

  subgraph SYNC ["Cross-Host File Synchronization"]
    SM["dev-bricks/sync-master\n(file-sync)"]
  end

  AGENTS -->|1. Check Locks| LM
  AGENTS -->|2. Route Requests| TM
  AGENTS -->|3. Evaluate Intent| BYUM
  AGENTS -->|4. Discover Profiles| CC
  CC -->|Loads Packs| SK
  AGENTS -->|5. Store Memory & State| HB
  LM -->|Guards Access| HB
  TM -->|Provides Routing| HB
  AGENTS -->|6. Align Machines| SM
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7. Multi-Agent Operational Lifecycle Sequence

The sequence below depicts the end-to-end execution flow of an AI coding agent performing a task within the agent-ops-stack operational harness:

sequenceDiagram
  autonumber
  participant User as User / Operator
  participant Agent as AI Coding Agent (CLI)
  participant LockMaster as lock-master (Locks)
  participant TicketMaster as ticket-master (Tickets)
  participant BYUM as build-your-users-mind (Avatar)
  participant ControlCenter as controlcenter-mcp (MCP)
  participant Homebase as homebase-mcp (Runtime)

  User->>Agent: Submit goal or code alteration task
  Agent->>TicketMaster: Check or create structured ticket (score & route)
  TicketMaster-->>Agent: Ticket confirmed & assigned
  Agent->>LockMaster: Verify project unlock & acquire lock (LOCK*.txt)
  LockMaster-->>Agent: Lock granted (exclusive edit boundary)
  alt Decision Needed & User Unreachable
    Agent->>BYUM: Query empirical decision-avatar
    BYUM-->>Agent: Grounded decision bounds & preferences
  end
  Agent->>ControlCenter: Discover MCP servers & resolve tool bundles
  ControlCenter-->>Agent: Bound MCP profile & available toolsets
  Agent->>Homebase: Persist task checkpoint & coordination state
  Agent->>Agent: Execute code modifications & run local test gates
  Agent->>TicketMaster: Mark ticket resolved & document evidence
  Agent->>LockMaster: Release lock & clean lockfile
  LockMaster-->>Agent: Project scope released
  Agent-->>User: Report completed execution & test results
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8. Governance & Runtime Invariants

The agent-ops-stack architecture operates under ten immutable governance and safety invariants to protect project trees from concurrent corruption and unbounded actions:

ID Governance Invariant Operational Rule Failure State Guarantee
01 100% Local-First & Zero Egress (INV-LOCAL-01) All coordination, manifests, and tooling execute strictly offline and locally. Zero telemetry egress or external API transmission.
02 Non-Elevation User-Mode (INV-USER-02) Every script, installer, and agent routine runs under unprivileged user rights. Elevation to administrative or root privileges is never requested.
03 Fail-Closed File Lock Integrity (INV-LOCK-03) Agents must check and honor lock-master LOCK*.txt before write actions. If a lock is active, mutating actions halt immediately.
04 Structured Ticket Routing (INV-ROUT-04) Open tasks and bugs must be dispatched via ticket-master protocols. Prevents silent or untracked changes across workspaces.
05 Empirical Decision-Avatar Fallback (INV-AVAT-05) Unclear design choices during operator absence consult build-your-users-mind. Prevents speculative deviations and unapproved architectural drifts.
06 Deterministic Manifest Blueprint (INV-MANI-06) Composition is strictly governed by agent-ops.manifest.json. Zero implicit dependencies; installer is purely declarative.
07 Immutable Release-Tag Pinning (INV-PIN-07) Manifest sources reference immutable release tags (v1.11.3, v2026.09.03). Eliminates upstream drift and unexpected breakages.
08 Sandboxed Installer Boundary (INV-SAND-08) install.sh clones modules exclusively into gitignored ./modules/. Zero mutation of user system or agent host configurations.
09 Cross-Device Slot-Gated Sync (INV-SYNC-09) sync-master assigns dedicated machine slots for multi-host alignment. Prevents split-brain sync collisions and cloud race states.
10 48h Security & Triage SLA (INV-SLA-10) Vulnerabilities and coordination faults adhere to prompt acknowledgment & triage. Acknowledged within 48h; triage within 5 business days.

9. How an Agent Uses This Stack

When entering an unfamiliar workspace or starting an operational session, an agent follows this structured procedure:

  1. Before modifying any file: Check for an active LOCK*.txt in the target project via lock-master. If locked, treat the scope as read-only.
  2. Permissions & scopes: If the project specifies a lock-master permission profile, evaluate the planned operation against declared policies.
  3. Decisions under uncertainty: If the user is unavailable and an architectural judgment call is needed, query build-your-users-mind for empirical guidance.
  4. Task logging & routing: File defects, proposed enhancements, or delegate tasks through ticket-master to ensure traceability.
  5. Skill selection & MCP configuration: Consult skills for standardized workflows; use controlcenter-mcp to select tool bundles; persist state via homebase-mcp.
  6. Multi-device alignment: On multi-machine setups, adhere to sync-master host-slot conventions and daily synchronization routines before pushing changes.

Tip

Multi-Agent Coordination Best Practice: Always run lock-master checks before starting code modifications in any shared codebase, and use ticket-master for routing unresolved tasks across agent sessions or to the user.


10. Quickstart & Installation

Clone agent-ops-stack and execute the installer script to inspect or set up local modules:

# 1. Clone the composition repository
git clone https://github.com/ellmos-ai/agent-ops-stack.git
cd agent-ops-stack

# 2. Run the declarative installer (clones modules into ./modules/)
./install.sh

# 3. Optional: specify a custom target directory
./install.sh custom-modules-dir

install.sh reads agent-ops.manifest.json, clones the seven repositories, and displays a comprehensive wiring summary of all provided and consumed capabilities. It makes no destructive system changes and sets no environment variables.


11. Manifest Schema Specification

agent-ops.manifest.json implements the ellmos-stack-manifest-v1 specification:

{
  "schema": "ellmos-stack-manifest-v1",
  "name": "agent-ops-stack",
  "description": "Local-first coordination layer for one or more CLI coding agents...",
  "modules": [
    {
      "name": "ticket-master",
      "source": { "type": "github", "repo": "dev-bricks/ticket-master", "ref": "v1.11.3" },
      "kind": "coordination",
      "boundaries": { "net": "none", "paths": ["./"], "tools": [] },
      "wiring": { "provides": ["ticket-routing"], "consumes": [] }
    }
  ]
}
  • schema: Identifies specification version (ellmos-stack-manifest-v1).
  • modules: List of component specifications with git source, kind, and boundaries.
  • boundaries: Hard limits on network access, path scoping, and exposed tool patterns.
  • wiring: Declares exported capabilities (provides) and dependencies (consumes).

12. Sibling Ecosystem & Cross-Integration Matrix

agent-ops-stack serves as the central coordination hub connecting tooling across the ellmos-ai, dev-bricks, and open-bricks ecosystems:

Repository Organization Ecosystem Role & Integration
dev-bricks/ticket-master dev-bricks Position-0 issue routing, ticket scoring, and task delegation
dev-bricks/lock-master dev-bricks File locking (LOCK*.txt), rights evaluation, and concurrency guards
dev-bricks/sync-master dev-bricks Cross-machine slot synchronization and gated daily routines
ellmos-ai/build-your-users-mind ellmos-ai Empirical decision-avatar model derived from interaction history
ellmos-ai/skills ellmos-ai Portable AI skill library in standardized SKILL.md format
ellmos-ai/ellmos-controlcenter-mcp ellmos-ai MCP control plane, server discovery, and capability bundles
ellmos-ai/ellmos-homebase-mcp ellmos-ai Shared state, memory facade, and multi-agent coordination runtime
ellmos-ai/stacks ellmos-ai Shared manifest schemas, validation utilities, and ecosystem stack catalog
ellmos-ai/convergence-reconciler ellmos-ai Reciprocal code evaluation, variant transplantation, and Pareto fitness
ellmos-ai/ellmos-chat ellmos-ai Local-first chat and agent orchestration interface
dev-bricks/CareCenter-for-Codex dev-bricks Background maintenance, health monitoring, and SQLite optimization
open-bricks/open-bricks open-bricks Umbrella open-source developer tooling and standards collective

13. Search, SEO & Disambiguation

  • Canonical Identity: ellmos-ai/agent-ops-stack is a declarative, local-first multi-agent coordination stack composing file locking, ticket routing, user-decision avatars, skills, and an MCP control plane.
  • Disambiguation: Unrelated to cloud SaaS observability platforms (such as AgentOps.ai), generic AgentStack scaffolding, or remote LLMOps telemetry servers.
  • Keywords & Search Anchors: ellmos-ai agent-ops-stack, local CLI agent coordination stack, MCP control plane for coding agents, manifest-driven agent ops stack, lock-master ticket-master sync-master stack, zero-egress multi-agent harness, autonomous agent collision defense.

14. Security Model & Threat Mitigation

agent-ops-stack operates under a defense-in-depth security model specifically tailored for autonomous coding environments:

  • Strict Local-First Boundary (INV-LOCAL-01): All operations, manifests, and coordination artifacts exist purely on the local file system. Zero network sockets are opened, zero background telemetry packets are transmitted, and zero remote credentials are used.
  • Unprivileged RunAsInvoker Execution (INV-USER-02): All scripts (install.sh, tests, verification routines) execute strictly within user privileges without administrative or root elevation prompts.
  • Fail-Closed Locking Against Concurrency Corruption (INV-LOCK-03): Active locks created by lock-master immediately halt write attempts, preventing multiple agents from destroying source code via uncoordinated concurrent writes.
  • Isolated Module Sandboxing (INV-SAND-08): The declarative installer clones sibling repositories strictly into the local, gitignored ./modules/ directory, preventing pollution of system-wide paths, global python environments, or global agent configs.
  • Fast-Response Vulnerability Triage (INV-SLA-10): We commit to an initial acknowledgment within 48 hours and formal security triage within 5 business days for any reported coordination or security defects.

15. Third-Party Licenses & Transparency

agent-ops-stack maintains an exhaustive, auditable inventory of all runtime, development, and tooling dependencies in THIRD_PARTY_LICENSES.md.

Category Component / Dependency License Policy / Boundary
Runtime & Core Python standard library (json, re, pathlib, tomllib, typing) PSFL-2.0 100% Offline, Zero-Egress
Packaging & Build setuptools >= 61.0 MIT Local packaging build-backend
Testing & Contracts pytest >= 7.0.0 MIT Automated contract test harness
Linting & Hygiene ruff >= 0.1.0 MIT / Apache-2.0 Fast static analysis and formatting
Shell Automation POSIX Shell (install.sh) / git / jq System / GPL / MIT Non-elevated repository cloning

All dependencies are strictly permissive and comply with the project's zero-egress, local-first operational invariants.


16. Verification & Automated Test Suite

agent-ops-stack enforces strict integrity verification through static linting and automated parity test suites:

# 1. Run automated metadata, schema, and parity contract tests (31 tests passed | 100% green)
pytest -v

# 2. Validate linter standards
ruff check .

# 3. Check shell script syntax
bash -n install.sh

# 4. Validate manifest JSON
python -c "import json; json.load(open('agent-ops.manifest.json', encoding='utf-8'))"

For complete vulnerability reporting guidelines and response timelines, consult SECURITY.md.


17. Security Policy & SLAs

For vulnerability disclosure protocols, coordinated security reports, and response SLAs, see SECURITY.md:

  • Acknowledgment SLA: Within 48 hours.
  • Triage SLA: Within 5 business days.
  • Security Advisories: Coordinated privately via GitHub Security Advisories.

18. License & Liability / Haftung

This repository is distributed under the permissive MIT License. See LICENSE for details. Each composed module remains under its respective open-source license.

Dieses Projekt ist eine unentgeltliche Open-Source-Schenkung im Sinne der §§ 516 ff. BGB. Die Haftung des Urhebers ist gemäß § 521 BGB auf Vorsatz und grobe Fahrlässigkeit beschränkt. Die komponierten Module unterliegen jeweils ihrer eigenen Lizenz (siehe verlinkte Repositories).

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Manifest-driven composition of the local agent-ops ecosystem: ticket routing, locking, cross-machine sync, decision-avatar, skills, and an MCP control plane for CLI coding agents

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