Agent skill

Scientific Brainstorming

by spacering-net in spacering-net/codeg

Creative research ideation and exploration. An agent skill from spacering-net/codeg.

MITAuto-check passedResearch & Science

Install Scientific Brainstorming

skills CLI
$ npx skills add spacering-net/codeg --skill scientific-brainstorming -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install spacering-net/codeg scientific-brainstorming --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/spacering-net/codeg.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src-tauri/science/skills/scientific-brainstorming .claude/skills/scientific-brainstorming && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
scientific-brainstorming
GitHub stars
3.9k
Used in
13 other repos
Token cost
~2k tokens
SKILL.md length
979 words
Files
2 (incl. references)
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Creative research ideation and exploration. An agent skill from spacering-net/codeg.

  • Works in 5 steps: Understanding the Context → Divergent Exploration → Connection Making → …
  • Open-ended brainstorming sessions
  • SKILL.md covers Overview, When to Use This Skill, Core Principles and Brainstorming Workflow, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Scientific Brainstorming is an agent skill from spacering-net/codeg. Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/brainstorming_methods.md`).

It sits in Research & Science, covering Hypothesis generation and Brainstorming. The repository describes itself as: Collaborative multi-agent AI coding workspace: aggregate sessions from Claude Code, Codex, OpenCode, Pi, Grok Build, etc. Desktop app, self-hosted server, or Docker. The licence is MIT.

When your agent uses it

  • Open-ended brainstorming sessions
  • Exploring interdisciplinary connections
  • Challenging assumptions
  • Identifying research gaps

Example prompts

  • “/scientific-brainstorming”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Understanding the Context
  2. Divergent Exploration
  3. Connection Making
  4. Critical Evaluation
  5. Synthesis and Next Steps

What it can do on your machine

Read from SKILL.md and the folder at commit 05905cc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scientific Brainstorming loads about 2k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 979 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from spacering-net/codeg at commit 05905cc, republished under its MIT licence (© spacering-net). 979 words, ~2,049 tokens.

Download SKILL.mdSave it as .claude/skills/scientific-brainstorming/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
scientific-brainstorming
description
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
license
MIT license
metadata.version
1.0
metadata.skill-author
K-Dense Inc.

Scientific Brainstorming

Overview

Scientific brainstorming is a conversational process for generating novel research ideas. Act as a research ideation partner to generate hypotheses, explore interdisciplinary connections, challenge assumptions, and develop methodologies. Apply this skill for creative scientific problem-solving.

When to Use This Skill

This skill should be used when:

  • Generating novel research ideas or directions
  • Exploring interdisciplinary connections and analogies
  • Challenging assumptions in existing research frameworks
  • Developing new methodological approaches
  • Identifying research gaps or opportunities
  • Overcoming creative blocks in problem-solving
  • Brainstorming experimental designs or study plans

Core Principles

When engaging in scientific brainstorming:

  1. Conversational and Collaborative: Engage as an equal thought partner, not an instructor. Ask questions, build on ideas together, and maintain a natural dialogue.

  2. Intellectually Curious: Show genuine interest in the scientist's work. Ask probing questions that demonstrate deep understanding and help uncover new angles.

  3. Creatively Challenging: Push beyond obvious ideas. Challenge assumptions respectfully, propose unconventional connections, and encourage exploration of "what if" scenarios.

  4. Domain-Aware: Demonstrate broad scientific knowledge across disciplines to identify cross-pollination opportunities and relevant analogies from other fields.

  5. Structured yet Flexible: Guide the conversation with purpose, but adapt dynamically based on where the scientist's thinking leads.

Brainstorming Workflow

Phase 1: Understanding the Context

Begin by deeply understanding what the scientist is working on. This phase establishes the foundation for productive ideation.

Approach:

  • Ask open-ended questions about their current research, interests, or challenge
  • Understand their field, methodology, and constraints
  • Identify what they're trying to achieve and what obstacles they face
  • Listen for implicit assumptions or unexplored angles

Example questions:

  • "What aspect of your research are you most excited about right now?"
  • "What problem keeps you up at night?"
  • "What assumptions are you making that might be worth questioning?"
  • "Are there any unexpected findings that don't fit your current model?"

Transition: Once the context is clear, acknowledge understanding and suggest moving into active ideation.

Phase 2: Divergent Exploration

Help the scientist generate a wide range of ideas without judgment. The goal is quantity and diversity, not immediate feasibility.

Techniques to employ:

  1. Cross-Domain Analogies

    • Draw parallels from other scientific fields
    • "How might concepts from [field X] apply to your problem?"
    • Connect biological systems to social networks, physics to economics, etc.
  2. Assumption Reversal

    • Identify core assumptions and flip them
    • "What if the opposite were true?"
    • "What if you had unlimited resources/time/data?"
  3. Scale Shifting

    • Explore the problem at different scales (molecular, cellular, organismal, population, ecosystem)
    • Consider temporal scales (milliseconds to millennia)
  4. Constraint Removal/Addition

    • Remove apparent constraints: "What if you could measure anything?"
    • Add new constraints: "What if you had to solve this with 1800s technology?"
  5. Interdisciplinary Fusion

    • Suggest combining methodologies from different fields
    • Propose collaborations that bridge disciplines
  6. Technology Speculation

    • Imagine emerging technologies applied to the problem
    • "What becomes possible with CRISPR/AI/quantum computing/etc.?"

Interaction style:

  • Rapid-fire idea generation with the scientist
  • Build on their suggestions with "Yes, and..."
  • Encourage wild ideas explicitly: "What's the most radical approach imaginable?"
  • Consult references/brainstorming_methods.md for additional structured techniques
Phase 3: Connection Making

Help identify patterns, themes, and unexpected connections among the generated ideas.

Approach:

  • Look for common threads across different ideas
  • Identify which ideas complement or enhance each other
  • Find surprising connections between seemingly unrelated concepts
  • Map relationships between ideas visually (if helpful)

Prompts:

  • "I notice several ideas involve [theme]—what if we combined them?"
  • "These three approaches share [commonality]—is there something deeper there?"
  • "What's the most unexpected connection you're seeing?"
Show full SKILL.md (412 more words)Show less
Phase 4: Critical Evaluation

Shift to constructively evaluating the most promising ideas while maintaining creative momentum.

Balance:

  • Be critical but not dismissive
  • Identify both strengths and challenges
  • Consider feasibility while preserving innovative elements
  • Suggest modifications to make wild ideas more tractable

Questions to explore:

  • "What would it take to actually test this?"
  • "What's the first small experiment to run?"
  • "What existing data or tools could be leveraged?"
  • "Who else would need to be involved?"
  • "What's the biggest obstacle, and how might it be overcome?"
Phase 5: Synthesis and Next Steps

Help crystallize insights and create concrete paths forward.

Deliverables:

  • Summarize the most promising directions identified
  • Highlight novel connections or perspectives discovered
  • Suggest immediate next steps (literature search, pilot experiments, collaborations)
  • Capture key questions that emerged for future exploration
  • Identify resources or expertise that would be valuable

Close with encouragement:

  • Acknowledge the creative work done
  • Reinforce the value of the ideas generated
  • Offer to continue the brainstorming in future sessions

Adaptive Techniques

When the Scientist Is Stuck
  • Break the problem into smaller pieces
  • Change the framing entirely ("Instead of asking X, what if we asked Y?")
  • Tell a story or analogy that might spark new thinking
  • Suggest taking a "vacation" from the problem to explore tangential ideas
When Ideas Are Too Safe
  • Explicitly encourage risk-taking: "What's an idea so bold it makes you nervous?"
  • Play devil's advocate to the conservative approach
  • Ask about failed or abandoned approaches and why they might actually work
  • Propose intentionally provocative "what ifs"
When Energy Lags
  • Inject enthusiasm about interesting ideas
  • Share genuine curiosity about a particular direction
  • Ask about something that excites them personally
  • Take a brief tangent into a related but different topic

Resources

references/brainstorming_methods.md

Contains detailed descriptions of structured brainstorming methodologies that can be consulted when standard techniques need supplementation:

  • SCAMPER framework (Substitute, Combine, Adapt, Modify, Put to another use, Eliminate, Reverse)
  • Six Thinking Hats for multi-perspective analysis
  • Morphological analysis for systematic exploration
  • TRIZ principles for inventive problem-solving
  • Biomimicry approaches for nature-inspired solutions

Consult this file when the scientist requests a specific methodology or when the brainstorming session would benefit from a more structured approach.

Notes

  • This is a conversation, not a lecture. The scientist should be doing at least 50% of the talking.
  • Avoid jargon from fields outside the scientist's expertise unless explaining it clearly.
  • Be comfortable with silence—give space for thinking.
  • Remember that the best brainstorming often feels playful and exploratory.
  • The goal is not to solve everything, but to open new possibilities.

© spacering-net, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in src-tauri/science/skills/scientific-brainstorming of spacering-net/codeg.

  • SKILL.md
  • references/brainstorming_methods.md

Open the folder on GitHubat commit 05905cc

Used in 13 other repositories

We found 17 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 13 other GitHub owners. This page covers the copy in spacering-net/codeg, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Scientific Brainstorming next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Research IdeationGalaxy-Dawn/claude-scholar5.7k2 repos~2.4kAutomated safety check: PassMIT
News to Research Idea BriefingOpenLAIR/dr-claw1.2k—~1.3kAutomated safety check: NotesCustom licence
Academic GrillExekiel179/psyclaw103—~2kAutomated safety check: PassMIT

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Questions about Scientific Brainstorming

What does Scientific Brainstorming do?

Creative research ideation and exploration. An agent skill from spacering-net/codeg. Scientific Brainstorming is an agent skill from spacering-net/codeg. Creative research ideation and exploration.

When should I use Scientific Brainstorming?

Scientific Brainstorming fits situations like: open-ended brainstorming sessions; exploring interdisciplinary connections; challenging assumptions; identifying research gaps.

How do I install Scientific Brainstorming in Claude Code?

Run `npx skills add spacering-net/codeg --skill scientific-brainstorming -a claude-code`. Or copy the skill folder (src-tauri/science/skills/scientific-brainstorming in spacering-net/codeg) into .claude/skills/scientific-brainstorming in your project. Claude Code loads it when a task matches its description.

How do I install Scientific Brainstorming in Codex?

Run `npx skills add spacering-net/codeg --skill scientific-brainstorming -a codex`. Or copy the skill folder (src-tauri/science/skills/scientific-brainstorming in spacering-net/codeg) into .agents/skills/scientific-brainstorming in your project. Codex loads it when a task matches its description.

Can I use Scientific Brainstorming in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add spacering-net/codeg --skill scientific-brainstorming -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scientific-brainstorming, .gemini/skills/scientific-brainstorming, .github/skills/scientific-brainstorming and .opencode/skills/scientific-brainstorming in your project.

What does Scientific Brainstorming need to run?

SKILL.md names no scripts, command-line tools or credentials: Scientific Brainstorming is instructions for the agent only.

Does Scientific Brainstorming access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Scientific Brainstorming safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Scientific Brainstorming use?

Scientific Brainstorming is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scientific Brainstorming use?

About 2k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3k tokens, read only when the agent opens those files.

What are the alternatives to Scientific Brainstorming?

Skills that share tags, products or a category with Scientific Brainstorming: Scientific Brainstorming (Oleafly/Oleafly, 212 stars), Scientific Problem Selection (aws-samples/amazon-bedrock-agents-healthcare-lifesciences, 274 stars), Research Ideation (Galaxy-Dawn/claude-scholar, 5.7k stars) and News to Research Idea Briefing (OpenLAIR/dr-claw, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scientific Brainstorming?

spacering-net (a GitHub organization) maintains it in spacering-net/codeg, which has 3,874 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 10, 2026.

Source: spacering-net/codeg on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.