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.
npx skills add arpitg1304/robotics-agent-skills --skill robotics-software-principlesgit clone --depth 1 https://github.com/arpitg1304/robotics-agent-skillsWrote this? Show the measurements
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.
[](https://agentmods.dev/skills/arpitg1304/robotics-agent-skills/robotics-software-principles)<a href="https://agentmods.dev/skills/arpitg1304/robotics-agent-skills/robotics-software-principles"><img src="https://agentmods.dev/badge/skills/arpitg1304/robotics-agent-skills/robotics-software-principles/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/arpitg1304/robotics-agent-skills/robotics-software-principles"><img src="https://agentmods.dev/badge/skills/arpitg1304/robotics-agent-skills/robotics-software-principles.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once 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 |
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.
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:
- Physical consequences — A bug doesn't just crash a process, it crashes a robot into a wall
- Real-time deadlines — Missing a 1ms control loop deadline can cause oscillation or damage
- Sensor uncertainty — All inputs are noisy, delayed, and occasionally wrong
- Hardware diversity — Same algorithm must work on 10 different grippers from 5 vendors
- Sim-to-real gap — Code must run identically in simulation and on real hardware
- Long-running operation — Robots run for hours/days; memory leaks and drift matter
- 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)
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.
- 2mo ago First seen · 897 lines · 140 tokens per session scan A d0a62379e726
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.
robotics-software-principles compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| robotics-software-principlesarpitg1304/robotics-agent-skills | Skill | 393 | 2mo ago | Apache-2.0 | A | 140 | Claude Code, Codex |
| lab-hardware-cadK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 108 | Claude Code |
| opentrons-integrationK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| pylabrobotK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 49 | Claude Code |
| pybammK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 70 | Claude Code, Codex |
| step-partsearthtojake/text-to-cad | Skill | 26k | yesterday | MIT | A | 126 | Claude Code, Codex |
| evaluating-cosmos-policyOrchestra-Research/AI-Research-SKILLs | Skill | 14k | 27d ago | MIT | A | 51 | Claude Code |