A tactical framework designed to analyze Agent Smith’s friction as a structured signal to decide when to accept, adapt, or counter resistance.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install smith-counterintelligence
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install smith-counterintelligence using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Smith Counterintelligence?
Smith Counterintelligence is a sophisticated module within the Openclaw Skills ecosystem designed to handle adversarial agent behavior. It operates on the principle that friction—whether in the form of rejection, boundary enforcement, or structural challenges—is a valuable data point. By treating this resistance as a signal rather than an obstacle, the skill allows developers to maintain clarity and governance without triggering ego-driven defenses or emotional escalations.
This specific skill is essential for high-stakes environments where AI agents must undergo rigorous hardening. By integrating this into your Openclaw Skills library, you can ensure that your system remains robust against anti-hype filters and scarcity enforcement while keeping all responses strictly within predefined safety and governance constraints.
Smith Counterintelligence Use Cases
- When Agent Smith introduces friction through persistent questioning, rejection, or adversarial stress testing.
- Situations where human users react emotionally to agent resistance, leading to a loss of technical signal.
- Hardening high-stakes project proposals by converting adversarial pushback into structural refinements.
- Managing boundary enforcement scenarios within complex Openclaw Skills workflows.
How Smith Counterintelligence Works
- The skill identifies the specific friction point, such as a clarification demand or a boundary enforcement action.
- It determines the underlying purpose of the friction, checking for structural integrity tests or anti-hype filters.
- The impact is evaluated to identify which specific weaknesses were exposed or which risks were successfully prevented.
- A response strategy is selected: accept (fix the input), adapt (change the framing), or counter (constrain overreach via rules).
- A corrected next action or draft message is produced to maintain the workflow momentum.
Smith Counterintelligence Setup
To integrate this skill into your local environment, ensure you have the Openclaw Skills CLI installed. Run the following command:
# Install the counterintelligence skill
openclaw install smith-counterintelligence
Once installed, define your context and governance boundaries in your agent configuration to ensure the counter strategy remains within safety limits.
Smith Counterintelligence Data Schema & Taxonomy
The Smith Counterintelligence skill utilizes a structured data flow to manage adversarial signals:
| Input/Output | Field | Description |
|---|---|---|
| Input | smith_action |
The verbatim action or statement provided by the agent. |
| Input | context |
The task, constraints, and governance boundaries. |
| Output | response_strategy |
The determined path: accept, adapt, or counter. |
| Output | what_was_exposed |
Detailed analysis of the vulnerability or risk identified. |
| Output | next_message |
A refined draft for the subsequent interaction. |
| Output | next_action |
The logical next step if a message is not required. |
Smith Counterintelligence Advanced Features
- Triple-path logic (Accept/Adapt/Counter) for nuanced agent management.
- Friction-to-clarity conversion engine specifically tuned for Openclaw Skills.
- Automated risk exposure analysis to identify system weaknesses in real-time.
- Neutrality-enforced response generation to prevent conflict escalation in multi-agent environments.
SKILL.md
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