A guided implementation workflow that turns an approved design into code and tests using test-driven development, or TDD: writing tests as part of the development cycle.

Use it to implement tasks linked to approved design documents, create the corresponding tests, perform health checks, and update the project's progress record.

It checks that the task and design are ready first, then keeps implementation progress recorded and applies project rules for testing, code quality, commands, and isolation.

implement — Command by Zenobia000

Install

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.

agentmods

npx agentmods add commands/zenobia000/cursor-agentic-coding-template/implement

Clone the repo

git clone --depth 1 https://github.com/Zenobia000/cursor-agentic-coding-template

Made for: Cursor.

Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 1,230 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00016	$0.01230
Opus 5	$0.00008	$0.00615
Sonnet 5	$0.00003	$0.00246
Haiku 4.5	$0.00002	$0.00123

Measured 2d ago against content hash b3700cbf4205, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

implement 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

implement — 100% identical, 0 lines differ

.cursor/commands/implement.md · 70 lines

How it starts

The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.

💻 IMPLEMENT MODE (v3)

將設計藍圖轉化為功能齊全、經過測試、且高品質的程式碼。

1. PLAN 🎯 (規劃)

Objective

根據 tasks.md 中指定的任務和其關聯的 creative-*.md 設計文檔，以測試驅動開發 (TDD) 的方式，編寫產品程式碼和對應的測試，並持續更新 memory-bank/current/progress.md 來記錄進度。

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
測試優先: .cursor/rules/testing/overview.mdc
程式碼品質: .cursor/rules/backend/overview.mdc 或 .cursor/rules/frontend/overview.mdc
指令執行: .cursor/rules/isolation_rules/Core/command-execution.mdc
核心隔離: .cursor/rules/isolation_rules/main.mdc

Prerequisites Check

在開始編碼之前，請確保：

✅ 任務已設計: memory-bank/current/tasks.md 中的當前任務已關聯一個或多個 creative-*.md 設計文檔。
✅ 設計已批准: 相關的設計文檔已被用戶確認。
❌ Failure Action: 如果找不到對應的設計文檔，AI 必須拒絕編碼，並建議用戶先執行 /creative 來完成技術設計。

2. DO 実行 (執行)

Core Process

遵循一個嚴格的、包含健康檢查的測試驅動開發循環：

Step 0: 健康檢查 (Health Check)

檢查設計完整性: 讀取 tasks.md 所連結的 creative-*.md 文件。驗證設計文檔是否清晰、完整。
批判性思考: 如果設計文檔含糊不清 (e.g., "然後處理數據")，AI 必須要求更具體的設計細節。

Step 1: 記憶體互動 - 讀取 (Memory Interaction - Read)

讀取任務與設計: 從 memory-bank/current/tasks.md 讀取任務要求，從關聯的 creative-*.md 讀取詳細的技術設計。

Step 2: 迭代開發 (Iterative Development)

遵循 TDD:
1. 寫一個失敗的測試 (Red): 根據設計，為即將實現的最小功能單元編寫一個測試，並確認它因功能未實現而失敗。
2. 寫最少的程式碼讓測試通過 (Green): 編寫最簡潔的產品程式碼，恰好能讓該測試通過。
3. 重構 (Refactor): 在測試保護下，優化剛才編寫的程式碼。
重複此循環，直到任務的所有功能點都已實現。

Step 3: 記憶體互動 - 寫入與更新 (Memory Interaction - Write & Update)

寫入產品程式碼: 在專案的源碼目錄中創建或修改對應的檔案。
寫入測試程式碼: 在專案的測試目錄中創建或修改對應的測試檔案。
持續更新進度: 在每個重要的開發節點，更新 memory-bank/current/progress.md 文件，簡要說明進度。

3. CHECK ✓ (檢查)

Verification Checklist

功能符合設計: 實作的功能是否完全符合 creative-*.md 中的設計？
測試全部通過: 所有相關的測試是否都已通過？
記憶體同步: memory-bank/current/progress.md 是否已更新？

4. ACT 改善 (行動)

Finalization

向用戶報告: 在一個主要功能的實作完成後，向用戶報告。例如：「任務『用戶登入』已完成，包含完整的程式碼和 95% 的測試覆蓋率。」

Next Steps

完成一個實作任務後，繼續推進專案。

👉 Primary Next Step: 執行 /task-next，讓 PM 小助理建議下一個最高優先級的任務。
💡 Alternative: 如果所有任務都已完成，請執行 /reflect 指令，對整個實作階段進行一次全面的回顧。

Read the full file on GitHub · 70 lines

Changes

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 · 70 lines · 16 tokens per session scan A b3700cbf4205

Subscribe to this mod's changes

implement is a command published in the GitHub repository Zenobia000/cursor-agentic-coding-template (30 stars, last pushed 2mo ago), licensed MIT. It adds 16 tokens to every session and 1,230 once invoked, about $0.0001 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 2026-08-30.

Productivity Testing Writing and docs

implement