Communitygithub.com

team-agent-orchestration

Run team-based orchestration for agent squads using work items, ownership, agent Kanban, merge gates, and control pane handoffs. Use when coordinating an agent squad with work items, ownership, Kanban, and merge gates.

Was ist team-agent-orchestration?

team-agent-orchestration is a Claude Code agent skill that run team-based orchestration for agent squads using work items, ownership, agent Kanban, merge gates, and control pane handoffs. Use when coordinating an agent squad with work items, ownership, Kanban, and merge gates.

Funktioniert mitClaude CodeCodex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/team-agent-orchestration

In Ihrer bevorzugten KI fragen

Öffnet einen neuen Chat, in dem dieser Agent-Skill bereits geladen ist.

Dokumentation

Team Agent Orchestration

Use this skill when agents are being managed like a team rather than a single assistant. The purpose is to make team-based orchestration reliable: clear work items, explicit ownership, agent Kanban state, branch isolation, control pane visibility, and merge gates.

When To Activate

  • The task spans multiple agents, tools, harnesses, branches, or worktrees.
  • The user mentions team orchestration, agent Kanban, squad, conductor, control pane, manager, desktop app, Zellij, tmux, Hermes, Devin, Codex, Claude Code, or multi-agent work.
  • A project needs shared workflow state across people and agents.
  • Existing agent fan-out is producing output but not mergeable product.

Operating Model

Treat every agent as a teammate with a narrow contract:

  • Owner: the person or agent accountable for the work item.
  • Scope: files, branch, tool surface, and forbidden areas.
  • State: backlog, ready, running, review, blocked, merged, or archived.
  • Evidence: tests, screenshots, logs, review notes, or eval reports.
  • Merge gate: the exact condition that allows integration.

Agent Kanban

Use agent Kanban when work must be visible across sessions.

ColumnMeaningExit Criteria
BacklogCandidate work item, not yet shapedAcceptance criteria written
ReadyShaped and assignableOwner and branch/worktree assigned
RunningAgent is actively workingHandoff artifact and changed files exist
ReviewWork is complete but not mergedTests, diff review, and risk check pass
BlockedNeeds external input or failed gateBlocker has owner and next action
MergedIntegrated into mainlinePR merged or local main updated
ArchivedNo longer relevantReason recorded

Each card should fit this schema:

{
  "id": "agent-card-001",
  "title": "Build dynamic workflow skill",
  "owner": "codex",
  "state": "running",
  "branch": "product/dynamic-workflow-team-orchestration",
  "worktree": ".",
  "acceptance": [
    "Skill exists",
    "Tests cover required concepts",
    "Content artifact contains video and article angles"
  ],
  "merge_gate": "lint, focused tests, and catalog check pass",
  "handoff": "path/to/handoff.md"
}

Team-Based Orchestration Flow

  1. Shape the board: convert fuzzy ambition into work items with owners and merge gates.
  2. Pick execution mode: single-agent, dynamic workflow mode, dmux/tmux, worktree fan-out, or external desktop orchestrator.
  3. Assign boundaries: one owner per card, clear file scope, and no overlapping writes without an integrator.
  4. Run agents: each agent writes evidence and handoff notes, not just code.
  5. Review in sequence: tests first, then diff review, then security/risk checks, then content/product polish.
  6. Merge deliberately: one integrator resolves conflicts and updates the control pane or status artifact.
  7. Extract reusable skill: if the card pattern repeats, promote it into skills/.

Control Pane Requirements

A useful control pane for team orchestration should show:

  • Active work items and their agent Kanban state.
  • Owner, harness, branch, worktree, and last heartbeat.
  • Links to handoff artifacts, tests, screenshots, and PRs.
  • Blockers grouped by owner and unblock action.
  • Merge readiness by gate, not vibes.
  • Reusable workflow candidates that should become shared skills.

Do not add more automation until the operator can answer: who owns this, what changed, what gate failed, and what can safely merge?

Dynamic Workflow Compatibility

When a card needs dynamic workflow mode:

  • Put the task-local harness under the card owner.
  • Store inputs and outputs on the card.
  • Require an eval before moving from Running to Review.
  • Promote the harness to a shared skill only after repeat use.

Failure Modes To Watch

  • Agent soup: many agents running, no owner or merge gate.
  • Invisible work: useful output exists only in a chat transcript.
  • Board theater: a Kanban board exists but cards have no acceptance criteria.
  • Overlapping writes: parallel agents edit the same files without worktrees.
  • No product artifact: the process produces docs but no runnable or publishable surface.

Output Standard

Finish each orchestration pass with:

  • Board/card changes.
  • Merged or pending branches.
  • Tests and eval evidence.
  • Blockers with owner and next action.
  • New shared skill candidates.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

Verwandte Skills