NanoResearch is an autonomous AI research system that turns research ideas into executable experiments and LaTeX papers supported by results from real training runs. It is for researchers validating prototypes, running GPU experiments, generating benchmarks, analyzing logs, and preparing paper drafts. The catalogue add-ons support its research pipeline and agent workflows.
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 OpenRaiser/NanoResearch --skill nanoresearch-ideationgit clone --depth 1 https://github.com/OpenRaiser/NanoResearchWrote 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/openraiser/nanoresearch/nanoresearch-ideation)<a href="https://agentmods.dev/skills/openraiser/nanoresearch/nanoresearch-ideation"><img src="https://agentmods.dev/badge/skills/openraiser/nanoresearch/nanoresearch-ideation/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/openraiser/nanoresearch/nanoresearch-ideation"><img src="https://agentmods.dev/badge/skills/openraiser/nanoresearch/nanoresearch-ideation.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00014 | $0.00225 |
| Opus 5 | $0.00007 | $0.00112 |
| Sonnet 5 | $0.00003 | $0.00045 |
| Haiku 4.5 | $0.00001 | $0.00022 |
Grade A, and why
nanoresearch-ideation 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 11d 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.
What it actually says
Ideation Skill
Purpose
Search arXiv and Semantic Scholar for papers related to a research topic, perform gap analysis, and generate novel hypotheses.
Tools Required
search_arxiv: Search arXiv for paperssearch_semantic_scholar: Search Semantic Scholar for papers and citations
Input
topic: The research topic or question to investigate
Process
- Generate 5-8 diverse search queries from the topic
- Search arXiv and Semantic Scholar using each query
- Deduplicate and rank papers by relevance
- Analyze the collected papers to identify research gaps
- Generate 2-4 novel hypotheses that address the identified gaps
- Select the most promising hypothesis with justification
Output
Produces papers/ideation_output.json containing:
- Retrieved papers with metadata
- Survey summary
- Gap analysis
- Generated hypotheses
- Selected hypothesis with rationale
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.
- 11d ago First seen · 34 lines · 14 tokens per session scan A e3851aa3f660
nanoresearch-ideation is a skill published in the GitHub repository OpenRaiser/NanoResearch (1,365 stars, last pushed 16d ago), licensed MIT. It adds 14 tokens to every session and 225 once invoked, about $0.0001 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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