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Octocode Brainstorming

Community
bgauryy
octocode-brainstorming

Use when an idea needs disciplined exploration before building: generate options, test whether it is worth building, map adjacent solutions, challenge assumptions, narrow scope, or choose Build RFC / Prototype / Narrow / Park — even if nobody said brainstorm. Already decided to implement a specific plan → skip.

Overview

Publisherbgauryy
Repositoryoctocode
Skill nameoctocode-brainstorming
Stars
950
Forks
78
Bundled files
17
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 17 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by bgauryy on GitHub. Read the source before you install it.

Installation

Install the Octocode Brainstorming AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bgauryy/octocode/tree/main/skills/octocode-brainstorming
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bgauryy/octocode.git /tmp/octocode
mkdir -p .claude/skills
cp -r /tmp/octocode/skills/octocode-brainstorming .claude/skills/octocode-brainstorming
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Octocode Brainstorming in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Octocode Brainstorming on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Octocode Brainstorming is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Octocode Brainstorming

Evidence-grounded idea exploration. Flow: FRAME → DIVERGE → RESEARCH → CROSS-POLLINATE → STRESS-TEST → SYNTHESIZE → DECIDE.

Modes and lobby rules

  • Generate: create 6–10 angles, then validate the best 2–3. Validate: produce 2–4 reframings, then investigate deeply. Map: expand adjacent terms and landscape existing solutions.
  • Capture framing before judging. When direction, audience, or research surface is unclear, ask the user to choose before deep research.
  • Declare a Surface Plan: mark local, top resources/web, and repository/package/code evidence active or skipped with a reason.
  • Treat snippets and summaries as leads; cite exact sources or mark claims weak. Track claim → source → confidence → next query.
  • Cross-pollinate across each active surface and run Critical Architect, Visionary Entrepreneur, and Product lenses before verdict.
  • Recall potentially useful context first and validate it; capture only durable lessons that survive rebuttal.

Hard gate

Stop, recommend one option, and wait when the idea spans three unrelated spaces, active evidence stays thin after synonym retries, evidence materially conflicts, or delegation would exceed five workers.

Smart routes — load only what the current step needs

  • When framing the idea and diverging into angles, build the Surface Plan with references/tools.md; when code/repository/package evidence is active, load references/octocode.md — choose sources deliberately and delegate technical research correctly.
  • When generic results cannot prove momentum, crowdedness, publication, or shipped prior art, load references/trend-sources.md — add time-sensitive evidence without domain lock-in.
  • When cross-pollinating leads from one active surface into another, stay in references/tools.md and references/web-search-workers.md — carry each finding across surfaces instead of closing a surface early.
  • When stress-testing, load references/debate.md — run the three lenses and cross-examination before converging.
  • When research is substantial, multi-turn, or delegated, load references/hook-communication.md and run scripts/brainstorm-run.mjs — preserve a resumable claim/source/decision ledger.
  • When synthesizing and deciding, load references/output.md and score every prior-art claim with references/confidence.md; if the user approves a durable artifact, load references/brief-template.md — match chat brevity or saved decision depth.
  • When methods or source contracts are challenged, load references/grounding.md — make the process falsifiable.
  • When improving this skill, prefer octocode-graph-eval; otherwise load references/improve-loop.md — require measurable acceptance.

Related routes

  • Use octocode-rfc-generator for a Build verdict; octocode-research for technical evidence; octocode-graph-eval for measurable experiments.
  • Use octocode-skills when changing this skill folder.
  • Use octocode-subagent to dispatch and synthesize workers — see references/web-search-workers.md for the brainstorm-specific Scout/Aggregator/Checker topology and the five-worker ceiling.

Scripts — every one takes --help

ScriptRun whenHow
scripts/brainstorm-run.mjsresearch is substantial, multi-turn, delegated, or saved as a briefnode <skill_dir>/scripts/brainstorm-run.mjs start --idea "<idea>" --mode Validate, then checkpoint --run-id <id>, then finish --run-id <id>; hook --event <event> serves hooks/hooks.json; commands in references/hook-communication.md
scripts/serper-search.mjsvalidating web credentials at session startnode <skill_dir>/scripts/serper-search.mjs --check — broad Google results (SERPER_API_KEY)
scripts/tavily-search.mjsvalidating web credentials at session startnode <skill_dir>/scripts/tavily-search.mjs --check — curated/deeper research (TAVILY_API_KEY)
scripts/exa-search.mjsvalidating web credentials at session startnode <skill_dir>/scripts/exa-search.mjs --check — neural/category search (EXA_API_KEY)
  • Use the --check scripts for credential presence only; fetching and search output come from the host web tool. Default to querying every validated engine and consolidating, not a first-success ladder (references/tools.md).
  • All four scripts import the vendored scripts/octocode-config.mjs for Octocode home and env; never import @octocodeai/config, which is absent when this folder installs alone.

Output

Use TL;DR, Framings, Evidence by surface, What survived review, Verdict, Risks, Next, Sources. Always end with Sources — a consolidated list of every URL/path actually cited above with the claim it backs, even for chat-only answers never saved as a brief. Template: references/output.md and references/brief-template.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Octocode Brainstorming AI skill do?

Use when an idea needs disciplined exploration before building: generate options, test whether it is worth building, map adjacent solutions, challenge assumptions, narrow scope, or choose Build RFC / Prototype / Narrow / Park — even if nobody said brainstorm. Already decided to implement a specific plan → skip.

Why use Octocode Brainstorming on TypingMind?

Because you install it once and use it with any model. Octocode Brainstorming is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Octocode Brainstorming in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bgauryy/octocode/tree/main/skills/octocode-brainstorming. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Octocode Brainstorming?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Octocode Brainstorming?

As many as you like. As long as a model supports skills, you can use Octocode Brainstorming with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Octocode Brainstorming AI skill free?

Yes. It is published on GitHub by bgauryy under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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