robotics-software-principles

robotics-software-principles is a skill for Claude Code, Codex from arpitg1304/robotics-agent-skills. It costs 140 tokens per session (7,058 once invoked), scanned A, original, Apache-2.0.

Software design guidance for building modules and libraries for robots. It explains principles such as keeping each module focused, while accounting for real-time timing, noisy sensors, different hardware, simulation, and safety.

In plain words
What is it for?
Use it when designing robot modules, organizing a robotics codebase, making architecture decisions, reviewing robotics code, or building reusable robotics libraries.
Why use it?
Robotics software can cause physical damage when it fails, and it must keep working despite uncertain sensor data and varied hardware. These guidelines help structure code so changes and failures are easier to contain.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it when designing robot modules, organizing a robotics codebase, making architecture decisions, reviewing robotics code, or building reusable robotics libraries.

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Install with agentmods
npx agentmods add skills/arpitg1304/robotics-agent-skills/robotics-software-principles
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add arpitg1304/robotics-agent-skills --skill robotics-software-principles
Clone the repo
git clone --depth 1 https://github.com/arpitg1304/robotics-agent-skills

Made for: Claude Code, Codex.

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A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Per session 140 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,058 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00140 $0.07058
Opus 5.5 $0.00056 $0.02823
Sonnet 5.5 $0.00028 $0.01412
Haiku 4.5 $0.00014 $0.00706

Measured 2mo ago against content hash d0a62379e726, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

robotics-software-principles scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/robotics-software-principles/SKILL.md · 897 lines

How it starts

The opening of the file, as written. The whole thing — 897 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Robotics Software Design Principles

Why Robotics Software Is Different

Robotics code operates under constraints that most software never faces:

  1. Physical consequences — A bug doesn't just crash a process, it crashes a robot into a wall
  2. Real-time deadlines — Missing a 1ms control loop deadline can cause oscillation or damage
  3. Sensor uncertainty — All inputs are noisy, delayed, and occasionally wrong
  4. Hardware diversity — Same algorithm must work on 10 different grippers from 5 vendors
  5. Sim-to-real gap — Code must run identically in simulation and on real hardware
  6. Long-running operation — Robots run for hours/days; memory leaks and drift matter
  7. Safety criticality — Some failures must NEVER happen, regardless of software state

These constraints demand disciplined design. Below are principles that account for them.


Principle 1: Single Responsibility — One Module, One Job

Every module (node, class, function) should have exactly ONE reason to change.

Why it matters in robotics: A perception module that also does control means a camera driver update can break your arm controller. In safety-critical systems, this coupling is unacceptable.

# ❌ BAD: God module — perception + planning + control + logging
class RobotController:
    def __init__(self):
        self.camera = RealSenseCamera()
        self.detector = YOLODetector()
        self.planner = RRTPlanner()
        self.arm = UR5Driver()
        self.logger = DataLogger()

    def run(self):
        image = self.camera.capture()
        objects = self.detector.detect(image)
        path = self.planner.plan(objects[0].pose)
        self.arm.execute(path)
        self.logger.log(image, objects, path)
        # If ANY of these changes, you touch this class

# ✅ GOOD: Separated responsibilities with clear interfaces
class PerceptionModule:
    """ONLY responsibility: raw sensor data → detected objects"""
    def __init__(self, camera: CameraInterface, detector: DetectorInterface):
        self.camera = camera
        self.detector = detector

    def get_detections(self) -> List[Detection]:
        image = self.camera.capture()
        return self.detector.detect(image)

class PlanningModule:
    """ONLY responsibility: goal + world state → trajectory"""
    def __init__(self, planner: PlannerInterface):
        self.planner = planner

    def plan_to(self, target: Pose, obstacles: List[Obstacle]) -> Trajectory:
        return self.planner.plan(target, obstacles)

class ExecutionModule:
    """ONLY responsibility: trajectory → hardware commands"""
    def __init__(self, arm: ArmInterface):
        self.arm = arm

    def execute(self, trajectory: Trajectory) -> ExecutionResult:
        return self.arm.follow_trajectory(trajectory)

Read the full file on GitHub · 897 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 897 lines · 140 tokens per session scan A d0a62379e726

Subscribe to this mod's changes

robotics-software-principles is a skill published in the GitHub repository arpitg1304/robotics-agent-skills (393 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 140 tokens to every session and 7,058 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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