What is robot-perception?

A guide to building robot systems that understand the world through cameras, LiDAR, depth sensors, and motion sensors.

Use it when setting up sensors, processing images or 3D point clouds, calibrating equipment, detecting or tracking objects, combining sensor data, or running perception models on robot hardware.

It helps address common problems such as incorrect sensor alignment, unsynchronised data, delays, dropped frames, and unreliable robot vision.

robot-perception — Skill for Claude Code and Codex by arpitg1304

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 robot-perception

Clone the repo

git clone --depth 1 https://github.com/arpitg1304/robotics-agent-skills

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/arpitg1304/robotics-agent-skills/robot-perception/github.svg)](https://agentmods.dev/skills/arpitg1304/robotics-agent-skills/robot-perception)

Your own site

<a href="https://agentmods.dev/skills/arpitg1304/robotics-agent-skills/robot-perception"><img src="https://agentmods.dev/badge/skills/arpitg1304/robotics-agent-skills/robot-perception/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/arpitg1304/robotics-agent-skills/robot-perception"><img src="https://agentmods.dev/badge/skills/arpitg1304/robotics-agent-skills/robot-perception.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 181 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 14,833 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 warn 7 Sept 2026

SkillSpector: 5 findings, 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 Data Exfiltration · line 439
Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.

Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
high Data Exfiltration · line 446
Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.

Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
medium analysis-evasion · line 1
Suspicious Unicode normalization or mixed-script content

Fix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
medium Prompt Injection · line 588
Subtle instructions detected that may alter agent decision-making or introduce hidden biases.

Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
medium Excessive Agency · line 679
Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.

Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00181	$0.14833
Opus 5.5	$0.00072	$0.05933
Sonnet 5.5	$0.00036	$0.02967
Haiku 4.5	$0.00018	$0.01483

Measured 2mo ago against content hash 3e6bc70bdeb9, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

robot-perception 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/robot-perception/SKILL.md · 1,655 lines

How it starts

The opening of the file, as written. The whole thing — 1,655 lines — stays where its author put it; the contents beside it link to each section on GitHub.