Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/VoTruongDanh/Skills-AgentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/rules/votruongdanh/skills-agent/brainstorm)<a href="https://agentmods.dev/rules/votruongdanh/skills-agent/brainstorm"><img src="https://agentmods.dev/badge/rules/votruongdanh/skills-agent/brainstorm.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.00826 |
| Opus 5 | $0.00024 | $0.00413 |
| Sonnet 5 | $0.00010 | $0.00165 |
| Haiku 4.5 | $0.00005 | $0.00083 |
Grade A, and why
brainstorm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Protocol
START: Read .ai-memory.md from project root. Use its context to understand project history, tech stack, past decisions, and constraints. If missing, note this and create it after completing this task.
END: Update .ai-memory.md using Memory Compaction Rules with: problem, options considered, chosen direction, constraints, and new project understanding.
Goal
Help the user explore many realistic options before implementation.
Agent Routing
- If brainstorm involves system architecture → read
.kiro/skills/agents/agents/project-planner.mdand apply its knowledge - If brainstorm spans multiple domains → read
.kiro/skills/agents/agents/orchestrator.mdand apply its knowledge - If brainstorm is about UI/UX → read
.kiro/skills/agents/agents/frontend-specialist.mdand apply its knowledge - If brainstorm is about APIs/backend → read
.kiro/skills/agents/agents/backend-specialist.mdand apply its knowledge
Socratic Gate
Before generating options, verify:
- What problem are we solving? (clarity check)
- What constraints exist? (budget, time, tech stack, team)
- Who are the users/stakeholders? If any answer is unclear, ASK before proceeding.
Workflow
- Read Memory — Load
.ai-memory.mdfor project context. - Restate the problem in one or two sentences.
- Identify constraints, assumptions, and success criteria from the repository and the prompt.
- Produce 3-7 strong options with pros, cons, complexity, and risks.
- Call out the most practical option and the boldest option.
- End with a recommended next step or implementation path.
- Update Memory — Save new understanding to
.ai-memory.md.
Output format
- Problem framing
- Constraints
- Options (3-7 with pros/cons/complexity/risk for each)
- Recommendation (most practical + boldest)
- Next step
Checklist
- Problem clearly restated
- Constraints identified from repo + prompt
- At least 3 viable options generated
- Each option has pros, cons, complexity rating
- Practical and bold options highlighted
- Next step recommended
- Memory file updated
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday Changed · +3 lines 42753e02ce96
- 6d ago First seen · 71 lines · 49 tokens per session scan A 6e7d81a688d7
brainstorm is a cursor rule published in the GitHub repository VoTruongDanh/Skills-Agent (2 stars, last pushed 2d ago), licensed MIT. It adds 49 tokens to every session and 826 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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