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 jeonnoin-alt/Eureka --skill research-brainstorminggit clone --depth 1 https://github.com/jeonnoin-alt/EurekaWrote 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/jeonnoin-alt/eureka/research-brainstorming)<a href="https://agentmods.dev/skills/jeonnoin-alt/eureka/research-brainstorming"><img src="https://agentmods.dev/badge/skills/jeonnoin-alt/eureka/research-brainstorming/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/jeonnoin-alt/eureka/research-brainstorming"><img src="https://agentmods.dev/badge/skills/jeonnoin-alt/eureka/research-brainstorming.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00039 | $0.03798 |
| Opus 5 | $0.00019 | $0.01899 |
| Sonnet 5 | $0.00008 | $0.00760 |
| Haiku 4.5 | $0.00004 | $0.00380 |
Grade A, and why
research-brainstorming 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.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brainstorming Research Questions Into Rigorous Designs
Help turn research ideas into fully formed, pre-registered study designs through natural collaborative dialogue.
Start by understanding the current project context, then ask questions one at a time to refine the research question. Once you understand what you're studying, present the design and get user approval.
Anti-Pattern: "This Is Too Simple To Need A Design"
Every study goes through this process. A correlation check, a single model comparison, a parameter sweep — all of them. "Simple" analyses are where unstated hypotheses and post-hoc rationalization cause the most damage. The design can be short (a few sentences for truly simple studies), but you MUST present it and get approval.
Checklist
You MUST create a task for each of these items and complete them in order:
- Explore project context — check existing papers, data, prior results, research notes. For data specifically: identify the exact source, version, and preprocessing state available. If the user is unsure which version of the data exists, surface this gap before proceeding.
- Ask clarifying questions — one at a time, understand the research question, constraints, and what success looks like
- Examine the literature gap (with Devil's Advocate) — structured search for what has NOT been done, plus active search for contradictory evidence
- Elicit the null hypothesis — exact statement of H0, not just "no effect"
- Test falsifiability — what specific result would DISPROVE the hypothesis?
- Enumerate confounds (including data leakage) — list the 3 most likely confounding variables AND check for data leakage risks (temporal, subject-level, preprocessing, feature). See
docs/references/data-checklist.md§3 for the leakage taxonomy. - Assess statistical power — expected effect size, required sample size, power justification
- Pre-specify the primary outcome — exactly one primary outcome measure, chosen before seeing results
- Propose 2-3 study designs — with trade-offs and your recommendation
- Present the research design — in sections, get approval after each section
- Write the research design document — save to
docs/eureka/designs/YYYY-MM-DD-<topic>-design.md - Design self-review — check for placeholders, internal consistency, scope, ambiguity, and verify that null hypothesis and falsifiability criterion both exist
- Dispatch
design-document-reviewersubagent — fresh-eyes review of the design document against the 11 mandatory questions (9 scientific + 2 narrative framing) and placeholder/consistency checks. Block progression onIssues Found; fix and re-dispatch untilApproved - User reviews written design — ask user to review before proceeding
- Transition — invoke
eureka:hypothesis-firstto register the hypothesis
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 234 lines · 39 tokens per session scan A 08a049198897
research-brainstorming is a skill published in the GitHub repository jeonnoin-alt/Eureka (2 stars, last pushed 4mo ago), licensed MIT. It adds 39 tokens to every session and 3,798 once invoked, about $0.0002 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 2026-08-31.
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