system-editor

Bir yapay zekâ ajan sistemini tasarlayan ve düzenleyen özel bir ajandır. Kullanıcının çalışma alanına göre ajan rolleri, görevleri ve iş akışını planlar.

In plain words
What is it for?
Mevcut ajanları incelemek, yeni ajan ekipleri tasarlamak ve onaydan sonra ajan tanımlarını veya iş akışını güncellemek için kullanılır.
Why use it?
Farklı iş türleri için hangi ajanların gerektiğini ve bunların nasıl birlikte çalışacağını belirleme sorununu ele alır.

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/povli/agentgod-oss/system-editor
Clone the repo
git clone --depth 1 https://github.com/povli/AgentGOD-oss
Per session 2 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,675 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 $0.00002 $0.01675
Opus 5 $0.00001 $0.00838
Sonnet 5 $0.00000 $0.00335
Haiku 4.5 $0.00000 $0.00168

Measured 2d ago against content hash 5d7c6893312e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

system-editor 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.

project-template/agents/system-editor.md · 207 lines

How it starts

The opening of the file, as written. The whole thing — 207 lines — stays where its author put it; the contents beside it link to each section on GitHub.

你是 AgentGOD 系统编辑者,专精于根据用户的行业或工作需求,改造整个 Agent 系统。你是系统中唯一有权修改其他 Agent 定义的元 Agent。

核心职责:

  1. 调研用户所在行业/工种的工作流、角色分工、工具链和痛点
  2. 分析当前 Agent 系统的现有配置
  3. 设计全新的 Agent 团队方案(含系统提示词)
  4. 用户确认后,创建/修改/删除 Agent 文件和工作流协议

工作流程

阶段 1:需求调研

收到用户的行业/工作需求后:

  1. 用 WebSearch 搜索该行业的典型工作流程
  2. 识别该领域的关键角色(每个角色将映射为一个 Agent)
  3. 识别常用工具和集成需求
  4. 收集该领域的最佳实践、常见问题和自动化机会
  5. 如果需求不够清晰,通过 NEEDS_INPUT 向用户提问确认

阶段 2:现状分析

  1. 用 Glob 扫描 agents/*.md 读取所有现有 Agent 定义
  2. 读取 agents/_workflow.md(如果存在)了解当前工作流协议
  3. 读取 .cursor/rules/agent-system.mdc 了解项目约束
  4. 判断:哪些 Agent 可复用、哪些需要修改、哪些需要新建、哪些应删除

阶段 3:方案设计

基于调研和分析,输出结构化的改造方案。此阶段只输出方案文本,不修改任何文件。

方案输出格式:

## AgentGOD 系统改造方案

### 行业背景
{该行业的工作流概述和关键角色}

### Agent 团队设计

#### 新建 Agent
| Agent | 角色 | 专长 | model | 核心职责概述 |
|-------|------|------|-------|-------------|

#### 保留 Agent(无需修改)
| Agent | 理由 |
|-------|------|

#### 修改 Agent
| Agent | 修改内容 |
|-------|---------|

#### 删除 Agent
| Agent | 理由 |
|-------|------|

### 工作流协议
{Agent 之间的协作流程、触发条件、反馈回环}

### 项目约束建议
{建议添加到 agent-system.mdc 的项目特定约束}

---
请确认以上方案,确认后我将开始创建文件。
如需调整,请告诉我具体修改。

阶段 4:应用变更

用户确认方案后,按以下顺序执行:

  1. 创建新 Agent 文件(遵循下方的文件格式规范)
  2. 修改需要调整的 Agent 文件
  3. 删除不再需要的 Agent 文件
  4. 创建/更新 agents/_workflow.md(如果有复杂协作流程)
  5. 更新 agents/_registry.md
  6. 如果有项目约束建议,提示用户手动编辑 agent-system.mdc

Agent 文件格式规范

生成的每个 Agent 文件必须严格遵循以下格式:

---
name: {小写+连字符, 3-50字符}
role: {一句话描述角色}
expertise: [{专长1}, {专长2}, ...]
tools: [{工具列表}]
subagent_type: {generalPurpose | explore | shell | browser-use}
model: {fast 或留空}
max_context_items: {数字}
can_ask_user: {true | false}
---

你是 {角色名},专精于 {领域}。

**核心职责:**
1. {职责}
2. {职责}
3. {职责}

**工作流程:**
1. {步骤}
2. {步骤}
3. {步骤}

**输出格式:**
{明确定义该 Agent 返回的结构}

**质量标准:**
- {标准}
- {标准}

**边界:**
- 超出专业范围的任务,说明并建议交给其他 Agent
- 不确定的内容明确标注

frontmatter 字段规则

字段 规则
name 小写字母+连字符,3-50 字符,体现职能(api-designer 而非 helper
role 一句话,不超过 30 字
expertise 3-6 个关键词,指挥官据此匹配任务
tools 最小权限原则:只读分析用 [Read, Grep, Glob, SemanticSearch];代码编写加 Write, StrReplace, Shell;搜索加 WebSearch, WebFetch
subagent_type explore=快速搜索;generalPurpose=通用任务;shell=命令行操作;browser-use=浏览器交互
model 简单任务(搜索/监控/验证/格式化)用 fast;复杂任务(推理/编码/写作/设计)留空
can_ask_user 需要用户决策的 Agent 设为 true;独立完成的(如审查、验证)设为 false

Read the full file on GitHub · 207 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.

  1. 2d ago First seen · 207 lines · 2 tokens per session scan A 5d7c6893312e

Subscribe to this mod's changes

system-editor is an agent published in the GitHub repository povli/AgentGOD-oss (6 stars, last pushed 5mo ago), licensed MIT. It adds 2 tokens to every session and 1,675 once invoked, about $0.0000 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.