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 experiment-controllergit 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/experiment-controller)<a href="https://agentmods.dev/skills/cuhk-aim-group/neuroclaw/experiment-controller"><img src="https://agentmods.dev/badge/skills/cuhk-aim-group/neuroclaw/experiment-controller.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00144 | $0.01772 |
| Opus 5 | $0.00072 | $0.00886 |
| Sonnet 5 | $0.00029 | $0.00354 |
| Haiku 4.5 | $0.00014 | $0.00177 |
Grade A, and why
experiment-controller 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 8d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Experiment Controller
Overview
This skill implements the Literature/GitHub Search → Scheme Confirmation → Git Execution → Iterative Logging process for the NeuroClaw experiment-controller phase.
It acts as the Experiment Manager within the multi-agent framework:
- Reads the latest IDEA.md and METHOD.md from the workspace.
- Searches recent literature (multi-search-engine, arxiv-search, pubmed-search) and GitHub for reproducible experimental setups and open-source repositories that match the proposed architecture.
- Summarizes candidate schemes (hyperparameters, datasets, baselines, training protocols) and proposes the most suitable GitHub repo.
- Iteratively discusses with the user to confirm the exact scheme/repo.
- After confirmation: uses git-essentials/git-workflows to clone, dependency-planner to install environment, claw-shell to run the experiment (training/inference/ablation).
- After every run (or ablation), automatically records: setup details, metrics, logs, observations, and any issues.
- Saves everything in EXPERIMENT.md (with dated sections for each run).
Research use only — the output is a complete, reproducible EXPERIMENT.md ready for paper-writing and future replication.
Quick Reference (Experiment Flow)
| Step | Description | Output File |
|---|---|---|
| 1. Read & Parse | Load IDEA.md + METHOD.md | 01_idea_method_summary.md |
| 2. Literature & GitHub Search | Find matching setups & repos | 02_search_results.md |
| 3. Proposal | Recommend best scheme + repo | 03_proposal.md |
| 4. User Discussion | Confirm scheme/repo | 04_discussion.md |
| 5. Git Clone & Setup | Clone + install dependencies | 05_setup_log.md |
| 6. Run Experiment | Execute training/inference/ablation | 06_run_log_*.md (per run) |
| 7. Record Results | Append metrics + observations | EXPERIMENT.md |
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.
- 8d ago First seen · 140 lines · 144 tokens per session scan A 80b6f77e2d4d
experiment-controller is a skill published in the GitHub repository CUHK-AIM-Group/NeuroClaw (83 stars, last pushed 2d ago), licensed MIT. It adds 144 tokens to every session and 1,772 once invoked, about $0.0007 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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