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 agentmods add instructions/openraiser/nanoresearch/agents-mdgit 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/instructions/openraiser/nanoresearch/agents-md)<a href="https://agentmods.dev/instructions/openraiser/nanoresearch/agents-md"><img src="https://agentmods.dev/badge/instructions/openraiser/nanoresearch/agents-md.svg" alt="Measured on agentmods" 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 | $0.00809 | $0.00809 |
| Opus 5 | $0.00404 | $0.00404 |
| Sonnet 5 | $0.00162 | $0.00162 |
| Haiku 4.5 | $0.00081 | $0.00081 |
Grade A, and why
NanoResearch AGENTS.md 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 3d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NanoResearch — Codex Integration Mode
NanoResearch is an end-to-end autonomous AI research engine. In Codex integration mode, Codex should drive the existing pipeline rather than inventing a second workflow.
Core Goal
Given a research topic, NanoResearch should produce a resumable research workspace containing:
- literature artifacts
- planning artifacts
- runnable experiment code when needed
- execution or literature-analysis evidence
- figures
- a LaTeX paper draft
- review output and final exported assets
Pipeline
NanoResearch uses a 9-stage pipeline:
IDEATION -> PLANNING -> SETUP -> CODING -> EXECUTION -> ANALYSIS -> FIGURE_GEN -> WRITING -> REVIEW
Stage meanings:
ideation: literature search, gap finding, hypothesis or theme extractionplanning: experiment blueprint or survey blueprint generationsetup: environment and resource preparationcoding: runnable experiment generationexecution: local or SLURM-backed experiment executionanalysis: structured evidence extraction from outputsfigure_gen: figure generation for paper assetswriting: LaTeX paper draftingreview: critique, verification, and revision
Workspace Convention
Workspaces live under ~/.nanoresearch/workspace/research/.
A typical workspace contains:
{session_dir}/
├── manifest.json
├── papers/
├── plans/
├── experiment/
├── drafts/
├── figures/
├── output/
└── logs/
Reuse an existing workspace when the user asks to continue, inspect status, resume, or revise a prior run.
Paper Modes
Topic prefixes:
original: Topic->original_researchsurvey:short: Topic->survey_shortsurvey:standard: Topic->survey_standardsurvey:long: Topic->survey_long
Behavior:
- original research follows the full 9-stage pipeline
- survey modes skip experiment-heavy stages and use literature-grounded planning, writing, and review
- the prefix is parsed by the existing CLI and manifest logic; Codex should reuse that behavior
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.
- 3d ago First seen · 96 lines · 809 tokens per session scan A 977f1ee8565c
NanoResearch AGENTS.md is an instructions file published in the GitHub repository OpenRaiser/NanoResearch (1,361 stars, last pushed 9d ago), licensed MIT. It adds 809 tokens to every session, about $0.0040 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.
Other instructions, from other repositories
swarms CLAUDE.md
Claude Code instructions for kyegomez/swarms, covering claude.md — swarms framework guide, installation & setup, any provider supported by litellm works, project layout and core primitive: agent.
langgraphjs CLAUDE.md
Instructions for langchain-ai/langgraphjs, covering langgraphjs development guide, corridor security analysis, build & test commands, code style guidelines and library architecture.
strix AGENTS.md
AGENTS.md instructions for usestrix/strix, covering strix — agent guide, using strix from an agent and contributing to this repo.
langgraphjs AGENTS.md
Instructions for langchain-ai/langgraphjs, covering repository instructions and corridor security analysis.
wanaku CLAUDE.md
Instructions for wanaku-ai/wanaku, covering wanaku, core guidelines, quick start, build info and architecture.
station AGENTS.md
Instructions for dualverse-ai/station, covering agent.md, first principles, coding agent checklist, current project snapshot and setup and run.