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-design-patternsgit 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-design-patterns)<a href="https://agentmods.dev/skills/arpitg1304/robotics-agent-skills/robotics-design-patterns"><img src="https://agentmods.dev/badge/skills/arpitg1304/robotics-agent-skills/robotics-design-patterns/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-design-patterns"><img src="https://agentmods.dev/badge/skills/arpitg1304/robotics-agent-skills/robotics-design-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 179 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00120 | $0.04847 |
| Opus 5 | $0.00060 | $0.02423 |
| Sonnet 5 | $0.00024 | $0.00969 |
| Haiku 4.5 | $0.00012 | $0.00485 |
Grade A, and why
robotics-design-patterns 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 11d 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 — 610 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Robotics Design Patterns
When to Use This Skill
- Designing robot software architecture from scratch
- Choosing between behavior trees, FSMs, or hybrid approaches
- Structuring perception → planning → control pipelines
- Implementing safety systems and watchdogs
- Building hardware abstraction layers (HAL)
- Designing for sim-to-real transfer
- Architecting multi-robot / fleet systems
- Making real-time vs. non-real-time tradeoffs
Pattern 1: The Robot Software Stack
Every robot system follows this layered architecture, regardless of complexity:
┌─────────────────────────────────────────────┐
│ APPLICATION LAYER │
│ Mission planning, task allocation, UI │
├─────────────────────────────────────────────┤
│ BEHAVIORAL LAYER │
│ Behavior trees, FSMs, decision-making │
├─────────────────────────────────────────────┤
│ FUNCTIONAL LAYER │
│ Perception, Planning, Control, Estimation │
├─────────────────────────────────────────────┤
│ COMMUNICATION LAYER │
│ ROS2, DDS, shared memory, IPC │
├─────────────────────────────────────────────┤
│ HARDWARE ABSTRACTION LAYER │
│ Drivers, sensor interfaces, actuators │
├─────────────────────────────────────────────┤
│ HARDWARE LAYER │
│ Cameras, LiDARs, motors, grippers, IMUs │
└─────────────────────────────────────────────┘
Design Rule: Information flows UP through perception, decisions flow DOWN through control. Never let the application layer directly command hardware.
Pattern 2: Behavior Trees (BT)
Behavior trees are the recommended default for robot decision-making. They're modular, reusable, and easier to debug than FSMs for complex behaviors.
Core Node Types
Sequence (→) : Execute children left-to-right, FAIL on first failure
Fallback (?) : Execute children left-to-right, SUCCEED on first success
Parallel (⇉) : Execute all children simultaneously
Decorator : Modify a single child's behavior
Action (leaf) : Execute a robot action
Condition (leaf) : Check a condition (no side effects)
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.
- 11d ago First seen · 610 lines · 120 tokens per session scan A 9d911e5462ea
robotics-design-patterns is a skill published in the GitHub repository arpitg1304/robotics-agent-skills (356 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 120 tokens to every session and 4,847 once invoked, about $0.0006 per session on Opus 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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