Token导航 LogoToken导航TokenDH.com
待分类需要联网github未标认证来源可访问clear审计通过

intent-and-automation意图和自动化

Agent Skill

intent-and-automation 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

490

周安装

20

GitHub Stars

1

下载量

157
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:intent-and-automation(意图和自动化)
来源仓库:https://github.com/tracemem/tracemem-skills
仓库路径:skills/intent-and-automation
安装命令:
npx skills add https://github.com/tracemem/tracemem-skills --skill intent-and-automation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/tracemem/tracemem-skills --skill intent-and-automation

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。

  • 支持从来源仓库获取上下文,结合安装命令和原始 README 核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 适用于需要自动化处理代码协作流程的场景,提升开发效率。
  • 可结合项目实际框架和协作规范使用,避免误操作影响生产环境。

SKILL.md

Skill: TraceMem Intent and Automation Modes

Purpose

This skill explains how to choose the correct intent and automation_mode for a Decision Envelope. Correct classification is critical for potential policy checks and audit clarity.

⚠️ VALID AUTOMATION MODES - ONLY THESE 4 VALUES

When calling decision_create, the automation_mode parameter MUST be one of these exact values:

ModeDescriptionUse When
proposeAgent suggests, human decidesYou're gathering info or proposing actions
approveAgent executes after approvalYou need human confirmation before acting
overrideHuman overrides policyBreaking rules with explicit permission
autonomousAgent acts independentlyFully automated within policy bounds

INVALID values (these will cause errors):

  • manual, auto, full_auto, automated
  • assisted, interactive, human_required
  • semi_auto, supervised, monitored

When to Use

  • When calling decision_create and you need to populate the arguments.
  • When determining if a task requires human-in-the-loop (propose) or can be done automatically (autonomous).

When NOT to Use

  • Do not invent new automation modes. Stick to the strict list.

Core Rules

  • Intent is Hierarchical: Intents must be dot-separated strings ordered from general to specific (Category -> Entity -> Action). Example: customer.order.refund.
  • Automation Mode is Binding: The mode you select declares your authority level.

- propose: You will only read data and suggest actions. You will NOT write/execute. - approve: You will execute, but only after explicit human approval (often enforced by policy). - override: You are explicitly breaking a rule (requires high permission). - autonomous: You will execute immediately without human intervention.

Correct Usage Pattern

Choosing an Intent

Structure: <Domain>.<Entity>.<Action>

  • Good: security.access_log.scan, billing.invoice.void, support.ticket.reply.
  • Bad: scan_logs, fix_thing, decision_1.

Choosing Automation Mode - Decision Tree

START: What kind of operation?
│
├─ Read-only (no state changes)
│  ├─ Just gathering information → `propose`
│  └─ Pre-approved read operation → `autonomous`
│
├─ Write/Update/Delete (state changes)
│  ├─ Need human approval first → `approve`
│  ├─ Just suggesting changes → `propose`
│  └─ Fully automated operation → `autonomous`
│
└─ Breaking a policy rule
   └─ Human override required → `override`
  1. Are you just looking?

- Mode: autonomous (if read-only duties are pre-approved) or propose (if you are just gathering info for a human).

  1. Are you planning to change state (write/delete)?

- If you need permission first: Mode propose (stop after planning). - If you have permission but need confirmation: Mode approve (TraceMem might force this anyway). - If you are fully trusted logic: Mode autonomous.

Example

{
  "intent": "network.firewall.block_ip",
  "automation_mode": "autonomous",
  "actor": "security-agent-v2"
}

Common Mistakes

  • Using invalid automation_mode values: Using values like manual, auto, full_auto, assisted, or interactive will cause errors. ONLY use: propose, approve, override, or autonomous.
  • Mismatched Mode: interacting as propose but then trying to decision_write (TraceMem may block this or flag it as a violation).
  • Inconsistent Intents: Using user.create in one decision and create.user in another. Be consistent.
  • Inventing automation modes: The 4 valid modes are fixed. You cannot create custom modes.

Safety Notes

  • Policy Triggers: Policies are often attached to specific intents. Using the wrong intent might bypass safety checks or trigger unnecessary alarms.
  • Escalation: If you start as autonomous but policy returns requires_exception, you effectively switch to an approval flow. The initial mode was your *desired* mode.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenCode

27.95%
按下载量换算44

Antigravity

21.94%
按下载量换算34

Claude Code

17.03%
按下载量换算27

Gemini CLI

12.57%
按下载量换算20

Cursor

7.71%
按下载量换算12

windsurf

3.11%
按下载量换算5

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

继续浏览同类 Skills