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 Clawland-AI/Clawarm --skill agx-arm-codegengit clone --depth 1 https://github.com/Clawland-AI/ClawarmWrote 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/clawland-ai/clawarm/agx-arm-codegen)<a href="https://agentmods.dev/skills/clawland-ai/clawarm/agx-arm-codegen"><img src="https://agentmods.dev/badge/skills/clawland-ai/clawarm/agx-arm-codegen/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/clawland-ai/clawarm/agx-arm-codegen"><img src="https://agentmods.dev/badge/skills/clawland-ai/clawarm/agx-arm-codegen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00057 | $0.01644 |
| Opus 5.5 | $0.00023 | $0.00658 |
| Sonnet 5.5 | $0.00011 | $0.00329 |
| Haiku 4.5 | $0.00006 | $0.00164 |
Grade A, and why
agx-arm-codegen 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 1mo 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 — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
This skill generates runnable Python scripts that control AgileX robotic arms (NERO 7-DOF, Piper 6-DOF) using the pyAgxArm SDK. It does NOT execute motion directly — it produces code that the user runs on a machine with CAN connectivity to the arm.
When to Use
- User says "write code to control the arm", "generate a script to move the arm", "make the arm do X"
- User describes a motion sequence in natural language
- User asks for a "runnable script" or "Python code" for arm control
- User mentions NERO, Piper, or AgileX arm control
Code Generation Rules
1. Connection & Configuration
from pyAgxArm import create_agx_arm_config, AgxArmFactory
robot_cfg = create_agx_arm_config(
robot="nero", # "nero" (7-DOF) or "piper" (6-DOF)
comm="can",
channel="can0",
interface="socketcan",
)
robot = AgxArmFactory.create_arm(robot_cfg)
robot.connect()
2. Enable Sequence
CRITICAL: The robot MUST be enabled BEFORE switching modes. If disabled, mode switches will fail.
import time
time.sleep(1) # 1s delay before mode switch
robot.set_normal_mode()
time.sleep(1) # 1s delay after mode switch
while not robot.enable():
time.sleep(0.01)
robot.set_speed_percent(80) # 0–100, start low for testing
3. Motion Modes
Set the motion mode explicitly before every move_* call:
| Mode | Constant | Method | Use Case |
|---|---|---|---|
| Joint position | robot.MOTION_MODE.J |
robot.move_j([j1..jN]) |
Smooth joint-space motion |
| Joint fast | robot.MOTION_MODE.JS |
robot.move_js([j1..jN]) |
No smoothing — use with caution |
| Point-to-point | robot.MOTION_MODE.P |
robot.move_p([x,y,z,r,p,y]) |
Cartesian, non-linear path |
| Linear | robot.MOTION_MODE.L |
robot.move_l([x,y,z,r,p,y]) |
Straight-line Cartesian path |
| Arc | robot.MOTION_MODE.C |
robot.move_c(start, mid, end) |
Circular arc through 3 poses |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 195 lines · 57 tokens per session scan A 915442e5d204
agx-arm-codegen is a skill published in the GitHub repository Clawland-AI/Clawarm (10 stars, last pushed 8mo ago), licensed MIT. It adds 57 tokens to every session and 1,644 once invoked, about $0.0002 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 2026-08-31.
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