Oma Brainstorm logo

Oma Brainstorm

OrganizationPopular
first-fluke
oma-brainstorm

Explore goals, constraints, and alternative approaches before choosing a design. Use when the user requests ideation or design exploration.

Overview

Publisherfirst-fluke
Repositoryoh-my-agent
Skill nameoma-brainstorm
Stars
1.3K
Forks
149
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by first-fluke on GitHub. Read the source before you install it.

Installation

Install the Oma Brainstorm 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.
  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/first-fluke/oh-my-agent.git /tmp/oh-my-agent
mkdir -p .claude/skills
cp -r /tmp/oh-my-agent/skills/oma-brainstorm .claude/skills/oma-brainstorm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Oma Brainstorm 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 Oma Brainstorm 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 Oma Brainstorm 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.

Brainstorm - Design-First Ideation

Scheduling

Goal

Explore user intent, constraints, and alternative approaches before planning or implementation, then preserve an approved design for downstream planning.

Intent signature

  • User says they have an idea, want to brainstorm, compare approaches, explore concepts, or design before planning.
  • Request is ambiguous enough that implementation or task planning would be premature.

When to use

  • Exploring a new feature idea before planning
  • Understanding user intent and constraints before committing to an approach
  • Comparing multiple design approaches with trade-offs
  • When the user says "I have an idea" or "let's design something"
  • Before invoking /plan for complex or ambiguous requests

When NOT to use

  • Requirements are already clear and well-defined -> use oma-pm directly
  • Implementing actual code -> delegate to specialized agents
  • Performing code reviews -> use oma-qa
  • Debugging existing issues -> use oma-debug

Expected inputs

  • Early idea, ambiguous goal, product concept, design question, or set of constraints
  • Existing project context when the idea must fit a codebase or product direction
  • User preferences and approval gates

Expected outputs

  • Clarified intent and constraints
  • Two or three approaches as prose briefs (scenario, mechanism, residual risk) plus a comparison matrix and recommended option
  • Section-by-section approved design document
  • Blind-review issue list (Tier 1 resolved, Tier 2/3 resolved or explicitly deferred)
  • Saved design artifact before handoff to planning

Dependencies

  • Shared context loading, reasoning templates, clarification protocol, quality principles, and skill routing
  • Optional resources/triz-lite.md for contradiction-shaped approach seeding
  • Per-agent reviewer dispatch (e.g. qa-reviewer, architecture-reviewer) for the high-stakes blind-review escalation path
  • Downstream PM workflow for task decomposition after design approval

Control-flow features

  • Branches by ambiguity, user answers, approach comparison, and approval gates
  • Optional TRIZ-lite branch when a technical/UX contradiction blocks distinct approaches
  • Asks one question at a time
  • Blind review round before save; may dispatch fresh-context reviewer subagents for high-stakes designs (the only subagent-spawning path in this skill)
  • Stops before implementation or task planning

Structural Flow

Entry

  1. Confirm that the request is exploratory rather than ready for implementation.
  2. Load enough project context to understand constraints.
  3. Start with intent and constraints, not solutions.

Scenes

  1. PREPARE: Explore context and frame the design question.
  2. ACQUIRE: Ask clarifying questions one at a time.
  3. REASON: Generate two or three approaches with tradeoffs.
  4. VERIFY: Get user approval section by section, then run a blind review round (independent lenses critique without seeing each other's feedback) before saving.
  5. FINALIZE: Save design and transition to planning when appropriate.

Transitions

  • If requirements become clear and implementation-ready, transition to PM planning.
  • If user rejects an approach, revise before moving to detailed design.
  • If implementation pressure appears early, defer it until design approval.
  • If approaches collapse into knob-turning on one axis, load resources/triz-lite.md and reseed, then re-present prose briefs.

Failure and recovery

  • If the user cannot answer a question, propose assumptions and ask for confirmation.
  • If scope expands, split the design into smaller sections.
  • If alternatives collapse into one option, identify the real constraint causing that; use TRIZ-lite only when that constraint is a technical/UX contradiction.

Exit

  • Success: approved design exists and is ready for planning.
  • Partial success: open questions and assumptions are explicit.

Logical Operations

Actions

ActionSSL primitiveEvidence
Read context and ideaREADUser prompt and project context
Ask targeted questionsREQUESTClarification phase
Compare approachesCOMPARETradeoff matrix
Infer recommendationINFERRecommended option
Emit option-selection decisionCALL_TOOLoma state emit + oma state verify --checkpoint option-selection
Validate approvalVALIDATESection-by-section confirmation
Run blind reviewVALIDATEIndependent lens critiques, tiered issue list, Tier 1 resolution
Write design artifactWRITEdocs/plans/designs/ and memory
Transition to planNOTIFYHandoff summary

Tools and instruments

  • Context loading, reasoning templates, clarification protocol
  • Optional TRIZ-lite resource for contradiction seeding
  • Project memory and docs/plans/designs/ for persisted designs

Canonical workflow path

text
1. Ask one clarifying question at a time.
2. (Optional) If technical/UX contradiction or same-axis approaches only → resources/triz-lite.md.
3. Present 2-3 approaches as prose briefs, then matrix, then recommendation; get user pick, then emit and verify the `brainstorm.option-selection` L1 decision.
4. Design section by section with user approval, then blind review: 4-8 independent lenses critique the design; resolve Tier 1 issues (fresh-context reviewer subagents for high-stakes designs).
5. Save the approved design to `docs/plans/designs/` before handing off to planning.

Resource scope

ScopeResource target
MEMORYUser intent, assumptions, decisions
CODEBASEExisting project context when relevant
LOCAL_FSApproved design artifacts; optional TRIZ-lite appendix in design doc

Preconditions

  • The user is still exploring or the request is ambiguous.
  • The agent can ask clarifying questions before implementation.

Effects and side effects

  • Produces design decisions and persisted design docs.
  • Influences downstream planning but does not implement code.

Guardrails

  1. No implementation or planning before design approval - brainstorm produces a design document, not code or task plans
  2. One question at a time - ask clarification and approval questions through the available asynchronous question tool first, following ../_shared/core/clarification-protocol.md; fall back to a permitted question tool or plain text. Continue independent work while waiting, and never infer approval from silence or a preselected option.
  3. Always propose 2-3 approaches - mechanistically distinct when possible; label each tactical or structural. The recommended option defaults to structural and must address the root cause. Recommend tactical only for genuinely throwaway scope, not merely because of deadline or effort pressure; include trade-off analysis.
  4. Prose before matrix - explain each approach with scenario, plain-language mechanism, solves/leaves, and cost feel; then comparison matrix; then recommendation. Do not lead with matrix-only output
  5. Section-by-section design - present design incrementally with user confirmation at each step
  6. Blind review before save - mandatory unless the design is trivially small (1-2 files, low stakes); lenses critique independently; use fresh-context reviewer subagents for architecturally significant, hard-to-reverse, or security-/compliance-sensitive designs
  7. YAGNI - do not over-engineer; design only what is needed for the stated goal
  8. TRIZ-lite is optional - only for technical/UX contradictions or same-axis collapse; max 3–5 principles from the curated set; no fake scores, full TRIZ/ARIZ, or classical matrices; seeds feed Step 3 briefs and do not replace user approval
  9. Save design, then transition - persist the approved design document before handing off to /plan

Execution Phases

Follow the brainstorm workflow step by step:

  1. Phase 1 - Context: Explore the existing codebase and understand the project landscape
  2. Phase 2 - Questions: Ask clarifying questions one at a time to understand intent and constraints
  3. Phase 3 - Approaches: Optionally seed with TRIZ-lite when contradiction-shaped; present 2-3 prose approach briefs labelled tactical/structural, a matrix, and an engineering-first structural recommendation unless the work is genuinely throwaway
  4. Phase 4 - Design: Present the detailed design section by section, getting user approval at each step
  5. Phase 5 - Blind Review: Run 4-8 independent reviewer lenses on the design, consolidate into Tier 1/2/3 issues, resolve Tier 1 before save; escalate to fresh-context reviewer subagents for high-stakes designs. Skip only for trivially small designs (1-2 files, low stakes)
  6. Phase 6 - Documentation: Save the approved design to docs/plans/designs/ and project memory
  7. Phase 7 - Transition: Hand off to /plan for task decomposition

Common Pitfalls

  • Jumping to solutions: Asking "how" before fully understanding "what" and "why"
  • Too many questions at once: Overwhelming the user with a wall of questions
  • Single approach bias: Presenting only one option without alternatives
  • Matrix-only options: Dumping a trade-off table without scenario/mechanism prose so the user cannot choose
  • Same-axis "alternatives": Three intensities of the same knob (interval/TTL/debounce) presented as distinct approaches
  • TRIZ on everything: Loading triz-lite without a real contradiction, adding ceremony without better options
  • Over-engineering: Designing for hypothetical future requirements instead of stated needs
  • Skipping confirmation: Moving forward without explicit user approval on design decisions
  • Skipping blind review: Saving a non-trivial design without the independent critique round, or letting the design's author-context leak into escalated reviewer prompts

References

  • TRIZ-lite (optional Step 3 seeding): resources/triz-lite.md
  • Context loading: ../_shared/core/context-loading.md
  • Clarification protocol: ../_shared/core/clarification-protocol.md
  • Quality principles: ../_shared/core/quality-principles.md
  • Skill-to-agent mapping: ../_shared/core/skill-routing.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 Oma Brainstorm AI skill do?

Explore goals, constraints, and alternative approaches before choosing a design. Use when the user requests ideation or design exploration.

Why use Oma Brainstorm on TypingMind?

Because you install it once and use it with any model. Oma Brainstorm 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 Oma Brainstorm in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/first-fluke/oh-my-agent/tree/main/skills/oma-brainstorm. 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 Oma Brainstorm?

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 Oma Brainstorm?

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

Is the Oma Brainstorm AI skill free?

Yes. It is published on GitHub by first-fluke 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇