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reflex-arc

Zero-cost cognitive immune system for AI agents. Fires automatic pre-response reflexes that catch contradictions, scope drift, hallucinations, overengineering, and tone mismatches BEFORE output reaches the user. Makes every other skill better by upgrading the bot's core reasoning quality. No APIs, no services, no cost — pure meta-cognition.

Why use this skill?

Enhance your AI agent with Reflex Arc, a zero-cost cognitive immune system that automatically prevents hallucinations, scope drift, and logic errors before output.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/jcools1977/reflex-arc
Or

What This Skill Does

Reflex Arc acts as a zero-cost cognitive immune system for your AI agent. Much like a biological reflex, it provides a built-in mechanism to audit, prune, and verify the agent's output before it is delivered to the user. By implementing a multi-stage heuristic check (the Six Reflexes), Reflex Arc systematically identifies and resolves common LLM failure modes such as hallucination, scope drift, internal contradictions, and over-engineering. It functions entirely through internal reasoning, requiring no external APIs or services, making it a highly efficient meta-cognitive upgrade for any AI workflow.

Installation

You can integrate Reflex Arc into your OpenClaw environment by running the following command in your terminal: clawhub install openclaw/skills/skills/jcools1977/reflex-arc

Use Cases

Reflex Arc is essential for scenarios where precision and reliability are non-negotiable. It is best utilized in:

  • Technical Engineering: Ensuring code snippets adhere strictly to the requested architecture without adding unasked-for bloat.
  • Complex Reasoning Tasks: Maintaining logical consistency across long-form answers where contradictions often creep into lengthy explanations.
  • Support Environments: Providing precise, direct answers that prevent 'over-answering' when the user simply needs a factual confirmation.
  • Strategic Decision Making: Evaluating whether the agent's proposed path aligns strictly with the user's constraints rather than deviating into unnecessary side-tasks.

Example Prompts

  1. "Does the Python requests library support automatic retries by default, and provide a single-line answer?"
  2. "Compare the performance impacts of using Redis vs. Memcached for session storage in a high-concurrency Node.js application, keeping the answer under three bullet points."
  3. "Is the configuration file located in the /etc/nginx/ directory for this specific distribution?"

Tips & Limitations

To maximize the efficiency of Reflex Arc, ensure the agent has sufficient context for the task at hand. While the skill is highly effective at catching internal logic errors, it relies on the base model's knowledge. It is not an external fact-checking tool and cannot verify truth against real-time live data, but it is excellent at spotting when the agent's internal narrative conflicts with itself. Remember that the skill is designed for high-stakes, specific outputs; you should avoid enabling it on trivial tasks to conserve processing overhead.

Metadata

Stars1947
Views0
Updated2026-03-04
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-jcools1977-reflex-arc": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#meta-cognition#reasoning#logic#reliability#quality-control
Safety Score: 5/5

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