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 CUHK-AIM-Group/NeuroClaw --skill conn-toolgit clone --depth 1 https://github.com/CUHK-AIM-Group/NeuroClawWrote 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/cuhk-aim-group/neuroclaw/conn-tool)<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/conn-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/conn-tool/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/cuhk-aim-group/neuroclaw/conn-tool"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/conn-tool.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 103 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00112 | $0.01871 |
| Opus 5 | $0.00056 | $0.00936 |
| Sonnet 5 | $0.00022 | $0.00374 |
| Haiku 4.5 | $0.00011 | $0.00187 |
Grade A, and why
conn-tool scanned grade A with 1 finding 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 12d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.run(cmd, check=True) How it starts
The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CONN Tool
Overview
CONN is a MATLAB/SPM-based toolbox for comprehensive functional and effective connectivity analysis. It excels at ROI-to-ROI, seed-to-voxel, ICA-based network analysis, and psychophysiological interaction (PPI/gPPI) as well as Dynamic Causal Modeling (DCM).
This skill serves as the NeuroClaw interface-layer wrapper for the CONN Toolbox and strictly follows the hierarchical design:
- Check whether CONN Toolbox and dependencies (MATLAB + SPM) are installed.
- If missing → invoke
dependency-plannerto generate a safe installation plan. - Verify input data (typically preprocessed BOLD from
fmriprep-toolorhcppipeline-tool). - Generate a clear, numbered execution plan with exact commands, project setup, and analysis steps.
- Present the plan and wait for explicit user confirmation (“YES” / “execute” / “proceed”).
- On confirmation → delegate the entire CONN project setup and analysis to
claw-shell. - After completion, summarize connectivity matrices, statistical maps, and suggest next steps (e.g., visualization or
paper-writing).
Research use only.
Quick Reference
| Task | What needs to be done | Delegate to which tool skill | Expected output |
|---|---|---|---|
| Project setup | Create new CONN project from preprocessed data | claw-shell |
conn_*.mat project file |
| ROI definition & extraction | Define ROIs from atlas or seed regions | claw-shell |
ROI time series |
| Functional connectivity (ROI-to-ROI) | ROI-to-ROI correlation analysis | claw-shell |
Correlation matrices |
| Seed-to-voxel connectivity | Seed-based whole-brain correlation | claw-shell |
Seed-to-voxel maps |
| ICA network analysis | Group ICA + network component extraction | claw-shell |
ICA components + networks |
| PPI / gPPI | Psychophysiological interaction analysis | claw-shell |
PPI contrast maps |
| Effective connectivity (DCM) | Dynamic Causal Modeling | claw-shell |
DCM parameters & model comparison |
| Full connectivity pipeline | Preprocessed data → ROI definition → connectivity → statistics | claw-shell |
Complete CONN results + figures |
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.
- 12d ago First seen · 180 lines · 112 tokens per session scan A 928fd021723e
conn-tool is a skill published in the GitHub repository CUHK-AIM-Group/NeuroClaw (85 stars, last pushed 6d ago), licensed MIT. It adds 112 tokens to every session and 1,871 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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