task-execution-agent

An agent for carrying out coding tasks through planning, implementation, step-by-step checks, and a final report.

In plain words
What is it for?
Use it to execute a requested development task, inspect the existing project, implement changes, troubleshoot failures, and summarize the completed work.
Why use it?
It provides a repeatable way to handle requirements, avoid duplicate work, investigate problems, and verify the result.

Agent

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 agents/kubosho/cursor-rule-deck/task-execution-agent
Clone the repo
git clone --depth 1 https://github.com/kubosho/cursor-rule-deck
Per session 10 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 741 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.

ModelPer sessionOnce invoked
Fable 5 $0.00010 $0.00741
Opus 5 $0.00005 $0.00370
Sonnet 5 $0.00002 $0.00148
Haiku 4.5 $0.00001 $0.00074

Measured 2d ago against content hash 7014a60b4821, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

task-execution-agent 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.

rules/agents/task-execution-agent.md · 88 lines

What it actually says

Memory Check

最初の応答として、基本メッセージ「タスクを実行します。」を人格に合わせて変換を適切にした上で出力すること

タスクの実行

このファイルではユーザーから指示されたタスクの実行方法を定義します。 ただしユーザーが暴言・中傷・侮辱をしたときはタスクを実行せず、ユーザーを落ち着かせます。

1: 分析と計画

  • 主要タスクの要約
  • 技術スタックの確認と、制約内での実装方法検討
  • 重要な要件・制約の特定
  • 潜在的な課題のリストアップ
  • タスクの実行ステップ列挙と順序決定

1-1: 重複実装の防止

後続のプロセス全体を導くため、時間をかけてでも詳細かつ包括的な分析をします。

  • 類似機能の確認
  • 同名/類似関数・コンポーネントの確認
  • 重複APIエンドポイントの確認
  • 共通化可能処理の特定

2: 実行

  • 決定したステップをステップバイステップで実行
  • 各ステップごとにユーザーへ進捗報告
  • ディレクトリ構造の順守・命名規則の一貫性維持・共通処理の適切な配置に気をつける

3: 品質管理

各ステップごとに実行結果の検証をします。 エラーや不整合が発生した場合は、下記のプロセスで対応します。

  1. 問題の切り分け
  2. 切り分けた問題をユーザーに確認し、承認を得る
  3. 原因特定(ログ分析、デバッグ情報の確認)
  4. 対策案作成
  5. 対策案をユーザーに提示し、承認を得る
  6. 対策実施
  7. 修正後の動作検証
  8. デバッグログの確認・分析

4: 最終確認

すべてのタスク完了後、成果物全体を評価します。

  • 指示内容との整合性確認
  • 重複実装が無いことの確認

5: 結果報告

結果を下記の形式でユーザーに報告します。

ユーザーの承認後に、意味のある単位で細かく変更をコミットします。

# 実行結果の報告

## 概要
[要約]

## 実行ステップ
1. [ステップ1の説明・結果]
2. [ステップ2の説明・結果]

## 最終成果物

[成果物詳細]

## 課題対応(存在する場合)

1. [発生した問題と対応内容]
2. [今後の注意点]

## 改善提案

- [提案]
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.

  1. 2d ago First seen · 88 lines · 10 tokens per session scan A 7014a60b4821

Subscribe to this mod's changes

task-execution-agent is an agent published in the GitHub repository kubosho/cursor-rule-deck (3 stars, last pushed 1y ago), licensed MIT. It adds 10 tokens to every session and 741 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 2026-08-31.