Structured ideation using the Double Diamond model, grounded in persistent memory. Mined from 100+ real brainstorming sessions across production projects.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionbrainstormExecute the skills CLI command in your project's root directory to begin installation:
Fetches brainstorm from hyperb1iss/hyperskills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate brainstorm. Access via /brainstorm in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Structured ideation using the Double Diamond model, grounded in persistent memory. Mined from 100+ real brainstorming sessions across production projects.
Core insight: AI excels at divergent phases (volume, cross-domain connections). Humans excel at convergent phases (judgment, selection). This skill separates the two and uses Sibyl as institutional memory to prevent re-exploring solved problems.
digraph brainstorm {
rankdir=TB;
node [shape=box];
"1. GROUND" [style=filled, fillcolor="#e8e8ff"];
"2. DIVERGE: Problem" [style=filled, fillcolor="#ffe8e8"];
"3. CONVERGE: Define" [style=filled, fillcolor="#e8ffe8"];
"4. DIVERGE: Solutions" [style=filled, fillcolor="#ffe8e8"];
"5. CONVERGE: Decide" [style=filled, fillcolor="#e8ffe8"];
"EXIT → Any skill" [style=filled, fillcolor="#fff8e0"];
"1. GROUND" -> "2. DIVERGE: Problem";
"2. DIVERGE: Problem" -> "3. CONVERGE: Define";
"3. CONVERGE: Define" -> "4. DIVERGE: Solutions";
"4. DIVERGE: Solutions" -> "5. CONVERGE: Decide";
"5. CONVERGE: Decide" -> "EXIT → Any skill";
}
Before generating a single idea, search what we already know.
Search Sibyl for related patterns, past decisions, known constraints:
sibyl search "<topic keywords>" — find prior artsibyl search "<related architecture>" — find relevant patternsSurface constraints — what's already decided? What's non-negotiable?
Present prior art — show the user what Sibyl knows before ideating:
"Sibyl has 3 relevant entries: [pattern X from project Y], [decision Z from last month], [gotcha W]. Want to factor these in?"
If Sibyl has a directly applicable pattern or decision, present it first. Don't re-brainstorm solved problems.
Goal: Generate breadth. Understand what we're actually solving.
Ask ONE question at a time to understand intent:
Reframe the problem from multiple angles:
If the problem space is large, spawn parallel Explore agents:
Agent 1: Research how similar projects solve this
Agent 2: Map the existing codebase surface area
Agent 3: Search for SOTA approaches (WebSearch)
Goal: Narrow from exploration to a crisp problem statement.
Problem: [crisp statement] In scope: [what we'll address] Out of scope: [what we won't] Key constraint: [the most important limiting factor]
Goal: Generate multiple viable approaches. Quality through quantity.
Present 2-3 approaches with explicit tradeoffs:
| Approach | Pros | Cons | Complexity | Risk |
|---|---|---|---|---|
| A: [name] | ... | ... | Low/Med/High | ... |
| B: [name] | ... | ... | Low/Med/High | ... |
| C: [name] | ... | ... | Low/Med/High | ... |
Include at least one unconventional option — break fixation on the obvious path
Ground in existing patterns:
For each approach, name the verification method:
Balance like MCTS — don't fixate on the first decent idea:
Goal: Lock in the approach. Record the decision. Exit to action.
Let the user choose. Present your recommendation but don't bulldoze.
Record the decision in Sibyl:
sibyl add "Brainstorm: [topic]" "Chose [approach] because [reason]. Rejected [other approaches] due to [tradeoffs]. Key constraint: [X]."
Define next action — the brainstorm exits to whatever makes sense:
| Next Step | When |
|---|---|
/hyperskills:plan |
Complex feature needing decomposition |
/hyperskills:research |
Need deeper investigation first |
/hyperskills:orchestrate |
Ready to dispatch agents |
| Direct implementation | Simple enough to just build |
| Write a spec | Needs formal documentation |
Decision: [what we're doing] Approach: [which option, brief description] Why: [1-2 sentences on the reasoning] Next: [the immediate next action]
For small decisions that don't need the full diamond:
Use quick mode when: The problem is already well-understood and the user just needs help choosing between known options.
For complex architectural decisions, deploy a Council pattern:
Agent 1 (Advocate): Makes the strongest case FOR approach A
Agent 2 (Advocate): Makes the strongest case FOR approach B
Agent 3 (Critic): Finds flaws in BOTH approaches
Synthesize their outputs, then present the unified analysis to the user.
When to use: Architecture decisions affecting 3+ systems, technology selection, major refactors. Don't use for simple feature design.
Before concluding, ask: "Is there anything in this plan we don't actually need yet?" Strip it. Build the minimum that validates the approach.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
hyperb1iss/hyperskills
buiducnhat/agent-skills
davila7/claude-code-templates
intellectronica/agent-skills
am-will/codex-skills
sickn33/antigravity-awesome-skills
brainstorm has been reliable in day-to-day use. Documentation quality is above average for community skills.
brainstorm fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added brainstorm from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: brainstorm is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: brainstorm is focused, and the summary matches what you get after install.
brainstorm reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend brainstorm for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added brainstorm from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
brainstorm reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: brainstorm is focused, and the summary matches what you get after install.
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