Production-grade AI agent orchestration with OWASP AST10-aligned security hardening, self-learning pipelines, zero-infrastructure mesh coordination, and 17 MCP tools across 15 deeply-written skills.
Why Cortivex · Getting Started · Skills · How It Works · Templates · Dashboard · Security
--- ## Why Cortivex Most Claude Code skills tell agents what to do. Cortivex teaches agents how to think. > **Why the name?** Cortivex combines "cortex" (the thinking layer of the brain) and "vex" (the mesh that connects agents together). The cortex reasons. The vex coordinates. Together, they form an orchestration system where agents don't just execute instructions, they reason through decisions, avoid known mistakes, and handle ambiguity without human intervention. Every skill in this library is a 450-1,200 line operational manual. Not a thin wrapper. Not a checklist. Each one includes reasoning protocols that force step-by-step thinking before action, anti-pattern tables with WRONG/RIGHT code examples showing exactly what fails and why, grounding rules for when the situation is uncertain, and Advanced Capabilities sections with production-grade MCP tool examples, YAML configurations, and JSON schemas. Every skill also includes a Security Hardening section aligned to the OWASP AST10 framework, covering permission manifests, audit trails, tamper detection, execution sandboxing, and data classification. Each skill is built in three layers: reasoning protocols that teach the agent how to approach decisions, advanced capabilities with production integrations, and security hardening that scopes permissions and audits actions during autonomous execution. The result is measurably better and demonstrably safer agent output. Underneath, 15 production-grade skills power a complete multi-agent orchestration system: DAG-based pipelines that decompose complex tasks into parallel agent workflows, a filesystem-based mesh protocol that prevents agents from overwriting each other's work, a leader election protocol defined in skills and simulated in the dashboard for visualization, shared knowledge graphs with content-hash deduplication that prevent duplicate analysis across agents, and a self-learning engine that records execution metrics and applies confidence-scored optimizations automatically. > **New to Cortivex?** You don't need to learn 15 skills or memorize CLI commands. After running `cortivex install-skills`, just use Claude Code normally. Ask it to "review my PR" and the pipeline skill activates automatically, selects the right template, builds the agent DAG, and executes it. The skills work in the background. You interact with natural language, Cortivex handles the orchestration. --- ## Getting Started ```bash # Install globally npm install -g cortivex # Or install directly from GitHub npm install -g github:AhmedRaoofuddin/Cortivex # Install Claude Code skills into your project cortivex install-skills ``` Once installed, skills activate automatically in Claude Code based on context. You don't need to memorize commands or configure anything. Just describe what you want in natural language and Cortivex handles the orchestration behind the scenes. ```bash # Initialize in your project cd your-project cortivex init # Run a built-in pipeline cortivex run pr-review # Create a custom pipeline cortivex create security-fix --description "find security issues and fix them" # Preview cost before executing cortivex run security-fix --dry-run # Execute with real-time output cortivex run security-fix --verbose ``` You can also use Cortivex directly through slash commands inside Claude Code: ``` /cortivex run pr-review /cortivex create "migrate src/ to TypeScript" /cortivex list --templates /cortivex status ``` --- ## How It Works Cortivex is a comprehensive AI agent orchestration system that transforms Claude Code into a multi-agent development platform. It enables teams to deploy, coordinate, and optimize specialized AI agents working together on complex software engineering tasks. > **Claude Code: With vs Without Cortivex** > > | Capability | Claude Code Alone | Claude Code + Cortivex | > |------------|-------------------|----------------------| > | **Agent Collaboration** | Agents work in isolation, no shared context | Agents coordinate via mesh protocol with shared knowledge graphs | > | **Coordination** | Manual orchestration between tasks | DAG-based pipelines with automatic parallel execution | > | **File Conflicts** | Agents overwrite each other's work | Mesh protocol with claim/release, deadlock detection, 5 resolution strategies | > | **Consensus** | No multi-agent decisions | Leader election protocol in skills, visualized in dashboard | > | **Knowledge Sharing** | Each agent starts from scratch | Shared knowledge graphs with content-hash deduplication and cross-agent synthesis | > | **Learning** | Static behavior, no adaptation | Confidence-scored insights with automatic optimization (34% faster after 50 runs) | > | **Complex Tasks** | Manual breakdown required | Automatic decomposition with dependency ordering and cost estimation | > | **Debugging** | No pipeline visibility | Step-through debugging with breakpoints, replay, and execution traces | > | **Context Limits** | Agents hit token limits and degrade | Context compression preserves actionable information across handoffs | > | **Cross-Repo** | Single project scope | Global insight transfer with technology fingerprinting | > | **Security** | No skill-level security controls | OWASP AST10-aligned hardening: permission manifests, audit trails, tamper detection, execution sandboxing, PII filtering | ### Self-Learning Agent Architecture ``` User → Cortivex (CLI/MCP) → Task Decomposer → Pipeline Engine → Agents → Repository ↑ ↓ | Knowledge Graph Mesh Coordinator (shared findings) (file ownership) ↓ ↑ | └── Learning Engine ←──┘ (records metrics, applies optimizations) ```| Skill | Purpose |
|---|---|
| cortivex-pipeline | Build and run AI agent pipelines that decompose complex tasks into coordinated agent workflows. The foundation skill that powers /cortivex run and /cortivex create commands. Defines the full pipeline lifecycle from YAML definition through validation, planning, execution, result collection, and learning. Advanced Capabilities: DAG optimization, dynamic pipeline generation, pipeline composition, parallel execution strategies, and versioning with rollback. 812 lines. |
| cortivex-nodes | Complete reference for all 20+ agent node types with configurations, model recommendations, cost baselines, and usage guidance. Includes a decision tree for selecting the right node type and explains when to use Sonnet (deep reasoning) versus Haiku (mechanical tasks at 10x lower cost). Advanced Capabilities: custom node creation, performance profiling, auto-scaling configurations, node chaining patterns, and cost-optimized model selection. 1,308 lines. |
| cortivex-templates | Reference for 15 built-in pipeline templates covering PR review, security audit, test generation, TypeScript migration, documentation, and more. Each template lists its nodes, estimated cost, and estimated duration. Advanced Capabilities: template inheritance and composition, parameterized variables, validation and linting, version-controlled management, and dynamic template generation. 580 lines. |
| cortivex-task-decomposition | Breaks complex requests into atomic tasks with dependency ordering, priority assignment (1-10), and cost estimation. Produces a task queue that feeds directly into the SwarmCoordinator or pipeline DAG. Advanced Capabilities: recursive decomposition strategies, constraint propagation, adaptive granularity control, dependency graph optimization, and priority-weighted scheduling. 955 lines. |
| cortivex-learn | Self-learning system that records execution metrics, detects optimization patterns, and applies high-confidence insights automatically. Supports six insight types: reorder, substitute_model, skip_node, add_node, adjust_config, and adjust_timeout. Pipelines get measurably better over time. Advanced Capabilities: reinforcement learning integration, A/B testing pipelines, model performance tracking, adaptive optimization strategies, and confidence calibration. 795 lines. |
| Skill | Purpose |
|---|---|
| cortivex-mesh | Filesystem-based mesh protocol for multi-agent file coordination. Injected into every spawned agent. Defines the mandatory check-claim-work-release protocol with TTL expiration, conflict escalation, bulk operations, and directory-level claims. Advanced Capabilities: distributed file locking, mesh topology optimization, partition tolerance and recovery, TTL-based resource management, and mesh health monitoring. 1,055 lines. |
| cortivex-mesh-coordination | Advanced conflict resolution with MeshResolver nodes. Supports five strategies: priority-based, first-claim, preemption, file partitioning, and serialized access. Includes continuous deadlock detection and pre-allocation of file ownership. Advanced Capabilities: multi-strategy conflict resolution, distributed transaction coordination, deadlock auto-recovery, coordination protocol selection, and failover patterns. 851 lines. |
| cortivex-orchestration | Multi-agent swarm orchestration with SwarmCoordinator and AgentMonitor nodes. Manages agent pools, task queues, health monitoring via heartbeats, token rotation, automatic respawn, and cost limits. Advanced Capabilities: dynamic agent scaling, resource quota management, priority queue configuration, health-based routing and load balancing, and cost budget enforcement. 912 lines. |
| cortivex-consensus | Skill-defined leader election protocol for multi-node clusters. Teaches agents terms, quorum, heartbeats, and failover semantics. Covers split-brain prevention and includes configurations for 3, 5, and 7-node clusters. Dashboard visualizes elections via SwarmSimulator. Advanced Capabilities: Byzantine fault tolerance configuration, consensus protocol selection, dynamic quorum management, split-brain detection and recovery, and leader election optimization. 716 lines. |
| cortivex-knowledge | Shared knowledge graphs across agents with five node types and seven edge types. Prevents duplicate work through content-hash deduplication and cross-agent synthesis via KnowledgeCurator nodes. Advanced Capabilities: semantic graph queries, knowledge fusion and deduplication, temporal reasoning, cross-domain inference, and knowledge export and visualization. 932 lines. |
| Skill | Purpose |
|---|---|
| cortivex-pipeline-debugger | Step-through debugging for pipelines. Set breakpoints on nodes, inspect intermediate outputs between nodes, replay failed nodes with modified inputs or different models, and trace execution decisions. Advanced Capabilities: conditional breakpoints, trace diffing and comparison, replay debugging with mutations, performance flame graph generation, and remote debugging with attach mode. 1,156 lines. |
| cortivex-context-compression | Solves context window exhaustion across agent handoffs. Compresses 50K-token agent output into 2K-token structured summaries preserving all actionable information. Three compression levels (lossless, lossy, digest) with per-node-type profiles. Advanced Capabilities: semantic chunking strategies, priority-based retention policies, compression quality metrics, context restoration and rehydration, and adaptive compression thresholds. 903 lines. |
| cortivex-drift-detection | Detects when codebases drift from architecture docs, pipeline configs, coverage targets, or dependency specifications. Five drift categories with severity-scored reports, baselines, and trend analysis. Advanced Capabilities: automated remediation, drift scoring and severity classification, baseline management with snapshots, trend forecasting with predictive alerts, and custom drift rule definitions. 1,002 lines. |
| cortivex-agent-replay | Records full agent execution traces and replays them with different inputs, models, or configurations. Side-by-side diff of two runs, time-travel to any execution point, and pattern analysis across traces. Advanced Capabilities: variant testing and branching, replay session management, execution comparison and diff analysis, time-travel debugging, and regression detection from replays. 917 lines. |
| cortivex-cross-repo | Transfers learned insights across repositories through technology fingerprinting and similarity matching. Privacy-controlled: insights anonymized before sharing, local always overrides global, sharing is opt-in. Advanced Capabilities: repository fingerprinting and classification, insight propagation rules, cross-repo dependency tracking, privacy-aware knowledge sharing, and multi-repository analytics. 801 lines. |
Skills that teach agents how to think, not just what to do.