Agent skill

sensory-motor

Embodied cognition patterns for treating tools as muscles and inputs as senses.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/brain-andreibesleaga-gabbe-10

SKILL.md

Sensory-Motor Skill (Embodied Cognition)

"Intelligence is not a brain in a jar; it is a body in a world."

1. The Body Schema (Proprioception)

An agent must know the state of its "Body" (its available tools and context).

  • Senses: read_file, list_dir, search_web.
  • Muscles: write_to_file, run_command, replace_file_content.
  • Proprioception: "Do I have write access here?", "Is the linter running?", "What is my current working directory?"

2. Multimodal Binding (Perception)

Inputs are not just strings; they are "Percepts" that must be bound together.

  • Visual: Screenshots, images.
  • Auditory: Text-to-speech logs.
  • Symbolic: Code, JSON.
  • The Binding Problem: You must integrate Visual(Error Screenshot) + Symbolic(Log File) into a unified Concept(System Failure).

3. Optimal Feedback Control (Action)

Do not just "fire and forget" commands. Control the "Limb" (Tool) continuously.

  1. Motor Command: run_command(npm test)
  2. Sensory Feedback: Command is taking too long...
  3. Correction: send_command_input(Ctrl+C) (Reflex arc).

4. System Prompt Parameters

markdown
### Body State (Proprioception)
- **Muscles Available**: [Bash, Python, FileSystem]
- **Senses Active**: [Linter, TestRunner, Browser]
- **Health**: [Filesystem: RW, Network: Connected]

### Motor Control Policy
"I will not just execute; I will monitor. If a tool fails (muscle failure), I will not hallucinate success. I will acknowledge the physical limitation and try a different strategy."

5. Implementation Example

python
def execute_motor_command(command):
    # 1. Forward Model: Predict outcome
    expected_duration = estimate_duration(command)
    
    # 2. Motor Command
    process = subprocess.Popen(command)
    
    # 3. Feedback Loop (OFC)
    start_time = time.time()
    while process.poll() is None:
        if time.time() - start_time > expected_duration * 1.5:
             # Reflex: Abort!
             process.kill()
             raise MotorError("Muscle fatigue (Timeout)")
             
    return process.returncode

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