brainstorm▌
boshu2/agentops · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Purpose: Separate WHAT from HOW. Explore the problem space before committing to a solution.
/brainstorm — Clarify Goals Before Planning
Purpose: Separate WHAT from HOW. Explore the problem space before committing to a solution.
Four phases:
- Assess clarity — Is the goal specific enough?
- Understand idea — What problem, who benefits, what exists?
- Explore approaches — Generate options, compare tradeoffs, adversarial critique
- Capture design — Write structured output for
/plan
Quick Start
/brainstorm "add user authentication" # full 4-phase process
/brainstorm # prompts for goal
Execution Steps
Phase 1: Assess Clarity
If the user provided a goal string, evaluate it. Otherwise prompt for one.
Use AskUserQuestion with options to gauge clarity:
- clear — Goal is specific and actionable (e.g., "add JWT auth to the API")
- vague — Goal exists but needs narrowing (e.g., "improve security")
- exploring — No firm goal yet, just a direction (e.g., "something with auth")
If vague or exploring, ask follow-up questions to sharpen the goal before proceeding. Do NOT move to Phase 2 until you have a concrete problem statement (one sentence, testable).
Phase 2: Understand the Idea
Answer these questions (use codebase exploration as needed):
- What problem does this solve? — State the pain point in concrete terms.
- Who benefits? — End users, developers, operators, CI pipeline?
- What exists today? — Current state, prior art in the codebase, adjacent systems.
- What constraints matter? — Performance, compatibility, security, timeline.
Summarize findings before moving on. If anything is unclear, ask the user.
Phase 3: Explore Approaches
Generate 2-3 distinct approaches. For each:
- Name — Short label (e.g., "JWT middleware", "OAuth proxy", "Session cookies")
- How it works — 2-3 sentences
- Pros — What it gets right
- Cons — What it gets wrong or defers
- Effort — Rough scope (small / medium / large)
Phase 3b: Adversarial Critique
Before asking the user to choose, stress-test each approach:
For each approach, answer these red team questions (read references/red-team-checklist.md):
- What breaks first? — Under load, edge cases, or adversarial input
- What's the hidden cost? — Maintenance burden, technical debt, learning curve
- What assumption is wrong? — The unstated belief that makes this approach seem good
- Who disagrees? — What would a senior engineer with the opposite preference say?
Mark any approach that fails 2+ red team questions as HIGH RISK in the comparison.
If all approaches fail 2+ questions, generate a 4th "hybrid" approach addressing the weaknesses.
Present the comparison and use AskUserQuestion to let the user pick an approach or request a hybrid.
Phase 4: Capture Design
Generate a date slug: YYYY-MM-DD-<goal-slug> (lowercase, hyphens, no spaces).
Write the output file to .agents/brainstorm/YYYY-MM-DD-<slug>.md:
---
id: brainstorm-YYYY-MM-DD-<goal-slug>
type: brainstorm
date: YYYY-MM-DD
---
# Brainstorm: <Goal>
## Problem Statement
## Approaches Considered
## Selected Approach
## Open Questions
## Next Step: /plan
All five sections must be populated. The "Next Step" section should contain a concrete /plan invocation suggestion with the selected approach as context.
Create the .agents/brainstorm/ directory if it does not exist.
Termination
Phase 4 output written = done. No further phases, no loops.
Validation
After writing the output file, verify:
- File exists at the expected path
- All 5 sections (
Problem Statement,Approaches Considered,Selected Approach,Open Questions,Next Step: /plan) are present and non-empty
Report the file path to the user.
Examples
Example 1: Specific goal
User: /brainstorm "add rate limiting to the API"
Phase 1: Goal is clear — add rate limiting to the API.
Phase 2: Problem is uncontrolled request volume causing timeouts.
Benefits operators and end users. No rate limiting exists today.
Phase 3: Three approaches — token bucket middleware, API gateway,
per-route decorators. User picks token bucket.
Phase 4: Writes .agents/brainstorm/2026-02-17-rate-limiting.md
Example 2: Vague goal
User: /brainstorm "improve performance"
Phase 1: Goal is vague. Asks: "Which part? API response times,
build speed, database queries, or something else?"
User says: "API response times on the search endpoint."
Phase 2: Investigates search endpoint, finds N+1 queries.
Phase 3: Approaches — query optimization, caching layer, pagination.
Phase 4: Writes .agents/brainstorm/2026-02-17-search-performance.md
Troubleshooting
| Problem | Cause | Solution |
|---|---|---|
| Brainstorm loops in Phase 1 without advancing | Goal remains too vague after follow-up questions | Provide a concrete, testable problem statement (e.g., "reduce API search latency below 200ms" instead of "improve performance"). |
| Output file missing one or more required sections | Phase 4 was interrupted or the skill terminated early | Re-run /brainstorm with the same goal; verify all 5 sections (Problem Statement, Approaches Considered, Selected Approach, Open Questions, Next Step: /plan) are present in the output. |
.agents/brainstorm/ directory not created |
The skill could not create the directory (permissions or path issue) | Manually create it with mkdir -p .agents/brainstorm and re-run. |
/plan invocation in "Next Step" section is generic or incomplete |
The selected approach was not specific enough to generate a concrete plan command | Edit the output file to refine the selected approach, then craft a /plan invocation that includes the approach name and key constraints. |
| Brainstorm produces only one approach in Phase 3 | The problem space is narrow or the goal is overly constrained | Widen the goal slightly or explicitly ask for alternative approaches (e.g., "consider a caching approach and a query optimization approach"). |
See Also
- skills/plan/SKILL.md — Decompose the selected approach into actionable issues
Reference Documents
- references/red-team-checklist.md — Adversarial critique template for Phase 3b
How to use brainstorm on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add brainstorm
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches brainstorm from GitHub repository boshu2/agentops and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate brainstorm. Access the skill through slash commands (e.g., /brainstorm) or your agent's skill management interface.
Security & Verification Notice
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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ 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.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★37 reviews- ★★★★★Nikhil Harris· Dec 20, 2024
Keeps context tight: brainstorm is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Pratham Ware· Dec 4, 2024
I recommend brainstorm for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★James Harris· Nov 11, 2024
brainstorm is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Xiao Sharma· Oct 2, 2024
Useful defaults in brainstorm — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yash Thakker· Sep 25, 2024
Useful defaults in brainstorm — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Daniel Mensah· Sep 25, 2024
brainstorm fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Nikhil Gonzalez· Sep 9, 2024
Registry listing for brainstorm matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Xiao Reddy· Sep 1, 2024
brainstorm is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Nikhil Rahman· Aug 28, 2024
brainstorm fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Kaira Kapoor· Aug 20, 2024
Useful defaults in brainstorm — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
showing 1-10 of 37