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 danmartinez78/VectorClaw --skill skillgit clone --depth 1 https://github.com/danmartinez78/VectorClawWrote 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/danmartinez78/vectorclaw/skill)<a href="https://agentmods.dev/skills/danmartinez78/vectorclaw/skill"><img src="https://agentmods.dev/badge/skills/danmartinez78/vectorclaw/skill/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/danmartinez78/vectorclaw/skill"><img src="https://agentmods.dev/badge/skills/danmartinez78/vectorclaw/skill.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 | $0.00026 | $0.00826 |
| Opus 5.5 | $0.00010 | $0.00330 |
| Sonnet 5.5 | $0.00005 | $0.00165 |
| Haiku 4.5 | $0.00003 | $0.00083 |
Grade A, and why
vectorclaw-mcp 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 15d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
VectorClaw MCP
VectorClaw connects OpenClaw to an Anki / Digital Dream Labs Vector robot through MCP. It provides practical robot control primitives for speech, movement, camera capture, and status/sensor reads.
What you can do
- Speak text with
vector_say - Move and position with
vector_drive,vector_head,vector_lift - Capture camera images with
vector_lookandvector_capture_image - Read robot state with
vector_status,vector_pose,vector_proximity_status,vector_touch_status - Build look → reason → act workflows
Vision requirement for look → reason → act
For see → reason → act workflows, the agent must either be vision-capable itself (e.g., a VLM) or have access to a separate vision model/image-interpretation tool to analyze camera images before choosing actions.
Requirements
- Vector robot configured and reachable
- Wire-Pod running
- SDK configured at
~/.anki_vector/sdk_config.ini VECTOR_SERIALenvironment variable set
Quick setup
- Install package:
pip install vectorclaw-mcp - Configure SDK:
python3 -m anki_vector.configure - Export robot serial:
export VECTOR_SERIAL=your-serial - Add MCP server:
{
"mcpServers": {
"vectorclaw": {
"command": "python3",
"args": ["-m", "vectorclaw_mcp.server"],
"env": { "VECTOR_SERIAL": "${VECTOR_SERIAL}" }
}
}
}
Tool coverage
Hardware-verified core tools
vector_say, vector_drive_off_charger, vector_drive, vector_emergency_stop, vector_head, vector_lift, vector_look, vector_capture_image, vector_face, vector_scan, vector_vision_reset, vector_pose, vector_status, vector_charger_status, vector_touch_status, vector_proximity_status
Experimental tools
vector_animate, vector_drive_on_charger, vector_find_faces, vector_list_visible_faces, vector_face_detection, vector_list_visible_objects, vector_cube
Current limitations
- Charger return (
vector_drive_on_charger) requires the charger to be in Vector's recently-observed world model; callvector_scanfirst to ensure reliable docking (without a prior scan the command may time out with no robot motion) - Perception tools (
vector_find_faces,vector_list_visible_faces,vector_face_detection,vector_list_visible_objects) return empty results when vision modes are not active; vision modes are enabled automatically at connect but are disabled for the remainder of the session aftervector_vision_reset— reconnect to restore them - Visual interpretation of camera images requires the agent to be vision-capable (e.g., a VLM) or have access to a separate image-interpretation tool
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.
- 15d ago Changed b39b5ddf0611
- 2mo ago First seen · 88 lines · 26 tokens per session scan A 76fedd5a32ca
vectorclaw-mcp is a skill published in the GitHub repository danmartinez78/VectorClaw (21 stars, last pushed 16d ago), licensed MIT. It adds 26 tokens to every session and 826 once invoked, about $0.0001 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.
vectorclaw-mcp compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| vectorclaw-mcpdanmartinez78/VectorClaw | Skill | 21 | 16d ago | MIT | A | 26 | Claude Code, Codex |
| gke-compute-classesgoogle/skills | Skill | 22k | yesterday | Apache-2.0 | A | 83 | Claude Code, Codex |
| jetson-diagnosticNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 30 | Claude Code, Codex |
| holoscan-install-wheelNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 34 | Claude Code, Codex |
| offensive-z-waveSnailSploit/Claude-Red | Skill | 10k | 25d ago | MIT | A | 113 | Claude Code, Codex |
| doca-socket-relayNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | A | 236 | Claude Code, Codex |
| hsb-flashNVIDIA/skills | Skill | 3.9k | yesterday | Apache-2.0 | B | 94 | Claude Code |