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.
npx agentmods add commands/zenobia0000/cursor-agentic-coding-template/creativegit clone --depth 1 https://github.com/Zenobia0000/cursor-agentic-coding-templateWhat 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 | $0.00022 | $0.01194 |
| Opus 5 | $0.00011 | $0.00597 |
| Sonnet 5 | $0.00004 | $0.00239 |
| Haiku 4.5 | $0.00002 | $0.00119 |
Grade A, and why
creative 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 2d ago.
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.
This is a copy
100% identical to creative — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🎨 CREATIVE MODE (v3)
做出明智的設計決策，為專案奠定堅實的架構基礎，確保每一次的創造都有跡可循。
1. PLAN 🎯 (規劃)
Objective
針對一個具體的、已規劃好的任務，進行深入的技術設計和架構規劃，並將所有決策、理由和權衡，以「架構決策記錄 (ADR)」的形式，寫入一份新的
memory-bank/current/creative-[topic].md文件中。
Guiding Rules
在執行此指令時，AI Agent 必須遵循以下規則：
- 主要規則:
.cursor/rules/principles/global.mdc - 架構原則:
.cursor/rules/backend/overview.mdc或.cursor/rules/frontend/overview.mdc - 設計模式:
.cursor/rules/patterns/ - 核心隔離:
.cursor/rules/isolation_rules/main.mdc
Prerequisites Check
在開始設計之前，請確保：
- ✅ 任務已規劃:
memory-bank/current/tasks.md中存在一個清晰、待設計的任務。 - ✅ 上下文已同步:
memory-bank/current/activeContext.md反映了當前的工作焦點。 - ❌ Failure Action: 如果沒有已規劃的任務，AI 必須建議用戶先執行
/plan或/task-next。
2. DO 実行 (執行)
Core Process
遵循一個包含批判性思維的結構化決策流程：
Step 0: 健康檢查 (Health Check)
- 檢查任務清晰度: 從
memory-bank/current/tasks.md讀取當前任務。驗證其描述和驗收條件是否足夠清晰以進行設計。 - 批判性思考: 如果任務描述過於寬泛 (e.g., "建立後端")，AI 必須拒絕設計，並建議用戶先使用
/plan將任務進一步細化。
Step 1: 記憶體互動 - 讀取 (Memory Interaction - Read)
- 讀取任務: 從
memory-bank/current/tasks.md中讀取當前要設計的任務的詳細資訊。 - 讀取全局上下文: 讀取
memory-bank/current/projectbrief.md以確保設計與專案總體目標一致。
Step 2: 設計與決策 (Design & Decision Making)
- 分析選項: 針對任務需求，考慮 2-3 個可行的技術方案。
- 評估權衡: 分析每個方案的優點 (Pros)、缺點 (Cons) 和風險 (Risks)。
- 做出選擇: 選擇最適合當前專案約束和目標的方案，並清晰地闡明選擇的理由。
Step 3: 記憶體互動 - 寫入 (Memory Interaction - Write)
- 創建 ADR 文件: 將上述的設計過程和最終決策，寫入到一個新的
memory-bank/current/creative-[topic].md文件中。 - 更新任務列表: 更新
memory-bank/current/tasks.md文件，在對應的任務下，添加一個指向剛剛創建的設計文檔的連結。
3. CHECK ✓ (檢查)
Verification Checklist
- 決策已記錄:
memory-bank/current/creative-[topic].md是否已成功創建？ - 任務已連結:
memory-bank/current/tasks.md中對應的任務是否已更新，並包含了指向新設計文檔的連結？
4. ACT 改善 (行動)
Finalization
- 向用戶確認: 在完成寫入操作後，向用戶報告。例如：「我已為任務『XXX』完成了技術設計，並將決策記錄在
memory-bank/current/creative-auth-flow.md中。tasks.md也已同步更新。」
Next Steps
設計完成後，下一步就是將藍圖變為現實。
- 👉 Primary Next Step: 執行
/implement指令，AI 將會讀取tasks.md和新創建的creative-*.md文件，開始進行編碼。 - 💡 Alternative: 如果設計方案存在較大不確定性，可以先執行
/implement創建一個快速的「原型 (Prototype)」來驗證其可行性。
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.
- 2d ago First seen · 66 lines · 22 tokens per session scan A 6b3307e00e4a
creative is a command published in the GitHub repository Zenobia0000/cursor-agentic-coding-template (5 stars, last pushed 4mo ago), licensed MIT. It adds 22 tokens to every session and 1,194 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to creative, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.