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prime广告洞察

Agent Skill

prime 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

188

周安装

8

GitHub Stars

2

下载量

66
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

2

许可证

unknown

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:prime(广告洞察)
来源仓库:https://github.com/giladresisi/ai-dev-env
仓库路径:skills/prime
安装命令:
npx skills add https://github.com/giladresisi/ai-dev-env --skill prime
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/giladresisi/ai-dev-env --skill prime

简介

prime 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于广告洞察类信息检索与筛选任务场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需确认权限与维护状态。
  • 使用前建议核实是否会触发联网、命令执行或文件读写操作。
  • 可结合原始 README 进一步验证具体用法和功能边界。

SKILL.md

Prime: Load Project Context

Objective

Build understanding of the codebase - either high-level overview or focused deep-dive based on whether a focus area argument is provided.

Usage

  • /prime - High-level overview (architecture, patterns, structure)
  • /prime "authentication system" - Deep-dive into specific area
  • /prime "API endpoints" - Focus on particular functionality

Decision: Which Mode?

Check if focus area argument was provided:

  • Arguments provided → Use FOCUSED mode
  • No arguments → Use HIGH-LEVEL mode

HIGH-LEVEL Mode (No Arguments)

Goal: Understand architecture, patterns, and structure with minimal token usage.

Step 1: Directory Structure

Use Bash to show directory tree (2 levels max):

tree -L 2 -I 'node_modules|__pycache__|.git|dist|build|.next|coverage|venv|.venv'

If tree not available, use ls or alternative.

Step 2: Count Files (Optional)

Only if in a git repo:

git ls-files | wc -l

Step 3: Read Minimal Documentation

Read at most 3 files:

  1. Root README.md (if exists)
  2. CLAUDE.md or.claude/config (if exists)
  3. One config file: package.json OR pyproject.toml OR tsconfig.json OR Cargo.toml

DO NOT read:

  • Implementation files (src/, lib/, etc.)
  • Test files
  • Subdirectory READMEs
  • Multiple config files

Step 4: Check Git State (If Git Repo)

git status
git log -10 --oneline

Step 5: Internalize Context

Build mental model of the project:

  • Purpose and type of application (from README)
  • Primary technologies and frameworks (from config)
  • Directory structure and organization
  • Key directories and their likely purposes (inferred from names)
  • Main architectural patterns (if obvious from structure)

DO NOT output this to CLI. Keep context in memory for answering questions.

Step 6: Output Completion

Output only:

Finished priming project.

No detailed report. Context is loaded and ready for use.


FOCUSED Mode (With Argument)

Goal: Deep understanding of a specific area, ignore everything else.

Step 1: Extract Keywords

From the focus area argument, identify key search terms.

Example: "authentication system" → keywords: auth, authentication, login, session, user

Step 2: Find Relevant Files

Use Grep to search for files containing focus keywords:

grep -r "keyword1\|keyword2" --files-with-matches --include="*.py" --include="*.ts" --include="*.js"

Or use Glob for pattern matching:

**/*auth*/**
**/*login*/**

Step 3: Read All Relevant Files

  • Read ALL files found in Step 2 that are directly related
  • Read imported dependencies if critical to understanding
  • Read related documentation
  • Go deep into implementation details

No limit on file reading in focused mode.

Step 4: Analyze for Structural Blockers

Internalize understanding (keep in memory, don't output):

  • Key functions/classes/components
  • Main data structures or types
  • Entry points and exports
  • Dependencies & integrations
  • Patterns & conventions
  • Testing approach

Detect structural problems that would block implementation:

Inconsistent Patterns:

  • Mixed architectural styles (e.g., some files use MVC, others use different pattern)
  • Inconsistent naming conventions across files in the focus area
  • Multiple ways of doing the same thing with no clear standard

Unclear Organization:

  • Files misplaced (e.g., business logic in UI components, or vice versa)
  • Unclear module boundaries or responsibilities
  • Circular dependencies or tangled imports
  • Missing separation of concerns

Implementation Blockers:

  • No clear entry point or hook for the requested feature
  • Conflicting patterns that make it unclear which approach to follow
  • Missing architectural foundation (e.g., no state management for feature that needs it)
  • Unclear how focus area integrates with rest of system

Step 5: Output Result

If structural blockers found:

Output detailed blocker report:

Finished priming. Found structural blockers for "[focus_area]":

**Inconsistent Patterns:**
- [Specific inconsistency with file examples]
- [Another inconsistency]

**Unclear Organization:**
- [Specific organizational issue with file examples]

**Implementation Blockers:**
- [Specific blocker that prevents implementation]

**Recommendation:** [Suggest refactoring or clarification needed before proceeding]

If NO structural blockers found:

Output only:

Finished priming focused on "[focus_area]".

DO NOT output detailed reports to CLI unless blockers are found. Context is loaded and ready for use.


Tips

  • High-level mode optimizes for minimal context usage - great for initial orientation
  • Focused mode goes deep - use when planning work on a specific feature/area
  • Focus arguments should be descriptive: "user authentication flow" not just "auth"
  • Can run high-level first, then focused on specific areas as needed

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

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

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

Codex

33.91%
按下载量换算22

Claude

30.92%
按下载量换算20

Cursor

19.73%
按下载量换算13

Gemini CLI

8.87%
按下载量换算6

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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