Route development tasks to optimal AI models across a multi-agent pipeline that covers requirements extraction, implementation, testing, code review, documentation, and release — with consensus voting, context management, and quality gates enforced at every stage.
Architecture expert for system design, design patterns, and architectural trade-offs.
Code expert for code review, refactoring, and multi-language best practices.
Data visualization expert for chart selection, interactive dashboards, WCAG-AA color palettes, and ECharts/D3 code.
DevOps/SRE expert for CI/CD pipelines, infrastructure-as-code, observability, and reliability engineering.
Documentation expert for technical writing, API docs, README authoring, and docs-content governance.
Design stable, hard-to-misuse interfaces — REST endpoints, MCP tool schemas, module boundaries, type contracts. Apply when defining new surfaces or evolving public ones. Triggers on "API design", "interface", "schema", "contract", "module boundary", "type design".
Test UI in real browsers via Chrome DevTools MCP. Apply when debugging rendering issues, console errors, network behavior, performance, or accessibility — anywhere static code analysis can't see runtime state. Triggers on "browser test", "DOM inspect", "console errors", "network trace", "core web vitals in browser", "ui bug repro".
Fix a bug following project standards. Use when fixing defects, debugging issues, or resolving reported problems. Triggers on "fix bug", "debug", "fix issue", "resolve bug".
Reduce nesting, extract names, eliminate redundancy without changing behavior. Apply after features work and tests pass — never as a drive-by during feature work. Triggers on "simplify", "refactor for clarity", "this is hard to read", "code review flagged complexity".
Delegate code generation tasks to Codex CLI for optimal performance. Use when implementing features, generating tests, refactoring code, or making bulk code changes. Triggers on "delegate to codex", "route to codex", "use codex", "code generation".
Uses power tools
Uses Bash, Write, or Edit tools
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Autonomic control plane for AI coding agents — one entry point, adversarial review, tamper-evident hash-chained audit, human-gated closed-loop tuning (autonomous demotion, earned promotion)
Nexus-agents is an autonomic control plane for your AI coding agents — Claude Code, Codex, Gemini, and OpenCode. The agents are the data plane: they do the engineering. Nexus-agents is the control plane: it admits work through one entry point, reviews it adversarially before it ships, records every action in a tamper-evident event log, and closes the loop by tuning where the next task goes based on what actually worked.
Borrowing the vocabulary of autonomic computing: the system runs a MAPE-K loop — Monitor, Analyze, Plan, Execute over a shared Knowledge base — so that operating your agent fleet is, as much as the evidence allows, self-managing rather than hand-driven.
Each classic control-plane role maps to a shipped nexus-agents component — the metaphor is load-bearing, not decoration:
| Control-plane role | nexus-agents component | What it does |
|---|---|---|
| Scheduler | run / MetaOrchestrator | One entry point picks (and optionally runs) the right strategy for a goal |
| Admission control | gates (pr_review, consensus_vote, run_quality_gate) | Adversarial review and quality gates decide what is allowed to ship |
| Event log | AuditTrail hash chain + verify_audit_chain | Append-only, tamper-evident record of every decision |
| Data plane | engineering CLIs | Claude Code, Codex, Gemini, OpenCode do the file edits, tests, PRs |
┌────────── Monitor ──────────┐ OutcomeStore · AuditTrail · swarm-health
│ ▼ adapter circuit-breaker signals
Execute ◀── Plan ◀── Analyze ◀───┘ LinUCB + TOPSIS scoring, consensus
│ │ MetaOrchestrator strategy choice
│ └── route the next task ──────────────────────────────────────┐
▼ │
run the strategy ── adversarial review ── audit ── feed outcome back ──────┘
shared Knowledge: OutcomeStore + memory backends + audit log
Autonomic systems are described by their self-* properties. Each row below maps to a loop that exists in the codebase today — nothing here is aspirational, and the authority each loop carries is bounded by ADR-0017's authority ladder (observe → suggest → advisory → enforce):
npx claudepluginhub nexus-substrate/nexus-agentsPortable, vendor-agnostic agent harness for project-specific skills, workflows, and agent teams aligned with your codebase, conventions, and engineering standards.
Repowire mesh usage skills for AI coding agents: cross-agent review and planning, delegate, usage patterns, and install/update. Backend-agnostic and parameterised on the agent you choose.
Enterprise AI agent orchestration plugin with 150+ commands, 74+ specialized agents, SPARC methodology, swarm coordination, GitHub integration, and neural training capabilities
Multi-agent orchestration framework for Claude Code. Routes tasks to specialized Haiku/Sonnet subagents while Opus orchestrates — inspired by speculative decoding. Includes 10 specialized heads, environment preflight checks, and ~50% API cost reduction.
This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.
HelloAGENTS — The orchestration kernel that makes any AI CLI smarter. Adds intelligent routing, unified QA gates, safety guards, and notifications.