Use when a multi-agent round needs a pre-merge gate, pre-commit check, verification before push, or a PASS/FAIL decision after reconciliation.
EnglishUse when multi-agent work risks context overflow, memory growth, noisy logs, oversized handoffs, cross-session continuation, or parallel Codex and Gemini execution.
EnglishUse when a consequential decision needs adversarial review, opposing agent arguments, a second opinion via debate, or explicit trade-off analysis before implementation.
EnglishUse when multiple agents have completed a round and the user asks to reconcile outputs, compare Codex and Gemini, synthesize run results, identify conflicts, or decide what should be retried.
EnglishUse when a task needs single-agent self-correction across multiple iterations — write plan, execute, critique own output, revise plan, re-execute, until convergence or budget exhausted. Different from agent-debate (which is 2 agents arguing pro vs con); this is 1 agent looping over its own work.
EnglishUse when the user asks to update shared memory, initialize multi-agent memory, summarize decisions so far, identify open questions, or prepare a fresh session primer.
EnglishUse when the user asks to split a goal across Claude, Codex, or Gemini (gemini requests are rerouted - lane deprecated); plan a multi-agent run; break work into parallel agent tasks; or decompose a large task that needs bounded context handoffs. This is the generic multi-agent task splitter — writes .coord/plan.yml (a DAG) plus per-agent task files. NOT for research-domain routing that touches .research/, .paper/, or Zotero/Obsidian/NotebookLM ingest pipelines — for those, use research-hub-multi-ai instead (different artifact .coord/multiaiplan.md, research-hub-aware reconciliation).
English
AGENT SKILLS ATLASIncludes Agent Acceptance Gate, Agent Context Budget, Agent Debate, and other workflows.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLISupported by the Atlas install prompt. Skill-specific requirements vary.
Pack stats
What’s included
Agent Acceptance Gate
Use when a multi-agent round needs a pre-merge gate, pre-commit check, verification before push, or a PASS/FAIL decision after reconciliation.
Agent Context Budget
Use when multi-agent work risks context overflow, memory growth, noisy logs, oversized handoffs, cross-session continuation, or parallel Codex and Gemini execution.
Agent Debate
Use when a consequential decision needs adversarial review, opposing agent arguments, a second opinion via debate, or explicit trade-off analysis before implementation.
Agent Output Reconciler
Use when multiple agents have completed a round and the user asks to reconcile outputs, compare Codex and Gemini, synthesize run results, identify conflicts, or decide what should be retried.
Agent Plan Act Reflect
Use when a task needs single-agent self-correction across multiple iterations — write plan, execute, critique own output, revise plan, re-execute, until convergence or budget exhausted. Different from agent-debate (which is 2 agents arguing pro vs con); this is 1 agent looping over its own work.
Agent Shared Memory
Use when the user asks to update shared memory, initialize multi-agent memory, summarize decisions so far, identify open questions, or prepare a fresh session primer.
Agent Task Splitter
Use when the user asks to split a goal across Claude, Codex, or Gemini (gemini requests are rerouted - lane deprecated); plan a multi-agent run; break work into parallel agent tasks; or decompose a large task that needs bounded context handoffs. This is the generic multi-agent task splitter — writes .coord/plan.yml (a DAG) plus per-agent task files. NOT for research-domain routing that touches .research/, .paper/, or Zotero/Obsidian/NotebookLM ingest pipelines — for those, use research-hub-multi-ai instead (different artifact .coord/multiaiplan.md, research-hub-aware reconciliation).
Quick start
- Choose your skills. Select individual skills above, or choose the entire pack.
- Copy the install prompt. Use Copy install prompt above the list.
- Send it to your agent. Paste into your coding agent’s chat. Your agent reviews the source and guides the setup.
Try it with your agent
After installation, start with a request like:
Use the Agent Acceptance Gate skill to help with my task.
Ask me for the context you need before getting started.Requirements & license
- A coding agent that can access your project files and install skills.
- Your agent checks each skill’s instructions, dependencies, and permissions during setup.
- Reported license for the skills shown: MIT. The author’s terms apply.