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 skills/onebrain-ai/onebrain/researchnpx skills add onebrain-ai/onebrain --skill researchgit clone --depth 1 https://github.com/onebrain-ai/onebrainWrote 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/onebrain-ai/onebrain/research)<a href="https://agentmods.dev/skills/onebrain-ai/onebrain/research"><img src="https://agentmods.dev/badge/skills/onebrain-ai/onebrain/research.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 | $0.00093 | $0.01108 |
| Opus 5 | $0.00046 | $0.00554 |
| Sonnet 5 | $0.00019 | $0.00222 |
| Haiku 4.5 | $0.00009 | $0.00111 |
Grade A, and why
research 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 4d 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 — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research
Research a topic and save the findings as a structured note in your resources folder.
Usage: /research [topic]
Step 1: Clarify the Research Goal
If topic is provided, confirm scope. If not, ask:
What do you want to research?
Then ask:
What are you trying to figure out? (This helps me focus the research.)
Optional: ask depth preference:
- Overview : broad understanding, key points
- Deep dive : comprehensive, with sources and nuance
- Practical : focused on how-to and actionable takeaways
Step 2: Conduct Research
Search for information on the topic. Look for:
- Authoritative sources (docs, papers, established publications)
- Multiple perspectives if the topic is contested
- Practical examples or case studies
- Recent developments (note dates of sources)
Step 3: Synthesize
Before writing the note, synthesize what you found:
- What's the core answer to the user's question?
- What are the key concepts to understand?
- What's actionable or immediately useful?
- What's uncertain or contested?
Step 4: Choose Subfolder
- Glob existing subfolders in
[resources_folder]/*/ - Suggest a kebab-case subfolder based on the research topic (max 2 levels, e.g.
technology/ai) - Present to user: "I'd file this under
[resources_folder]/[suggested-path]/. OK?" Show existing subfolders as options. - Use confirmed path for file creation.
Step 5: Create Research Note
File: [resources_folder]/[subfolder]/[Topic Name].md (subfolder confirmed in Step 4)
If a note on this topic already exists (search recursively in [resources_folder]/**/*.md), ask whether to create a new one or append a "Research : [Date]" section.
---
tags: [research, topic-tag]
created: YYYY-MM-DD
source: /research
sources: [list of key sources]
---
# [Topic Name]
> **Research goal:** [What the user was trying to figure out]
## Overview
[2-3 sentence summary]
## Key Concepts
### [Concept 1]
[Explanation]
### [Concept 2]
[Explanation]
## Key Takeaways
- [Actionable insight 1]
- [Actionable insight 2]
- [Actionable insight 3]
## Open Questions
- [Something the research didn't fully resolve]
## Sources
- [Source 1 : title and context]
- [Source 2 : title and context]
## Related
[[Link to related vault notes]]
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.
- 4d ago First seen · 165 lines · 93 tokens per session scan A 50ea4cf7a8e2
research is a skill published in the GitHub repository onebrain-ai/onebrain (25 stars, last pushed 6d ago), licensed Apache-2.0. It adds 93 tokens to every session and 1,108 once invoked, about $0.0005 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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