Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).
Agentic Research Control Panel
Agentic Research Control Panel is an open-source workflow skill for Claude Code and Codex, published by JasonCodeMaker. Its author describes it as: “Local control plane for governed AutoResearch in real repos: human-approved scope, live experiment tracking, evidence-backed results, and project memory for Claude Code and Codex.”. The project has 6 stars on GitHub and does not declare a license, so check with the author before reuse. Add it to your setup with `git clone https://github.com/JasonCodeMaker/Agentic-Research-Control-Panel ~/.claude/skills/Agentic-Research-Control-Panel`.
Installation
Add Agentic Research Control Panel to your agent with:
git clone https://github.com/JasonCodeMaker/Agentic-Research-Control-Panel ~/.claude/skills/Agentic-Research-Control-PanelAlways review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.
When to use it
Reach for Agentic Research Control Panel when you want workflow help from Claude Code without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.
Strengths
- Declares compatibility with Claude Code, Codex
- Actively maintained (recent commits)
Things to check
- No license declared — confirm terms with the author before reuse
- Limited adoption so far — evaluate before depending on it
Topics
Frequently asked questions
- What does Agentic Research Control Panel do?
- Local control plane for governed AutoResearch in real repos: human-approved scope, live experiment tracking, evidence-backed results, and project memory for Claude Code and Codex.
- How do I install Agentic Research Control Panel?
- Run git clone https://github.com/JasonCodeMaker/Agentic-Research-Control-Panel ~/.claude/skills/Agentic-Research-Control-Panel in your agent, then reload your skills. Review the source at https://github.com/JasonCodeMaker/Agentic-Research-Control-Panel before installing.
- Is Agentic Research Control Panel free to use?
- Agentic Research Control Panel is publicly available on GitHub, but JasonCodeMaker has not declared a standard open-source license (No license). Confirm the terms with the author before reusing it.
- Which agents does Agentic Research Control Panel work with?
- Agentic Research Control Panel declares compatibility with Claude Code and Codex. Agent Skills use a portable SKILL.md format, so other compatible clients can usually load it too.
Related skills
More Workflow →Turn any domain folder of skills into a bounded agentic loop: compile a goal into a verifiable task plan, execute tasks with the domain's own tools, verify every task with machine-run checks, retry with caps, escalate to a human when budgets exhaust, and refuse to close until everything is verified or explicitly waived. Use when you want an agent or subagent to pick up a goal and drive it to a verified close across one of this repo's 18 domains ('run this goal through the engineering harness', 'set up an agentic loop for marketing work', 'make the finance domain self-verifying'). NOT for authoring Claude Code Workflow-tool .js scripts (workflow-builder), N-agent tournaments on one task (agenthub), single-file metric optimization (autoresearch-agent), or discovering published loop recipes (loop-library).
Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.
Use when the user asks to automate browser tasks, scrape websites, fill forms, capture screenshots, extract structured data from web pages, or build web automation workflows. NOT for testing — use playwright-pro for that.
Simple useful tools for dev workflow with AI