复制安装命令
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
This is the open-source content repository behind
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
This is the open-source content repository behind Skill Store. It stores every approved Agent Skill, the records that go with it, and the automated security audits published with each skill.
This repo is a companion to the Skill Store platform, not the place to submit skills. Skills are added through skillstore.io — its review pipeline writes to this repo automatically. Please do not open a pull request here to add a skill; PRs adding skills will be closed. See Contributing a skill below.
The recommended way to install any skill is the skillstore CLI — one command works for both Claude Code and Codex:
npx skillstore add author/skill-name
For example:
npx skillstore add aiskillstore/code-review
It downloads the skill and drops it into the right skills/ directory for your tool. Claude Code auto-discovers it; for Codex, restart the session.
Prefer to do it by hand, or installing via Claude Web? See the full Installation Guides for every method (CLI, manual, and ZIP upload) and the scope directories (~/.agents/skills/, .claude/skills/, ~/.claude/skills/, .codex/skills/, …).
Submit through the platform — not through a pull request:
SKILL.md.SKILL.md — the skill definition (required, per the Agent Skills spec)LICENSE (recommended)Every submission is scanned automatically before it can be published. The audit flags things like:
eval, exec, raw system commands)Security analysis is report-only: findings inform maintainers and users, but a risk result does not automatically block an otherwise approved skill from being published. See our Security Trust Center for the methodology, limitations, and risk-level definitions.
Live Security Passport example:
.
├── skills/ # Approved, published skills (one folder each, with SKILL.md)
├── pending/ # Submissions awaiting review
├── packages/
│ ├── cli/ # The `skillstore` CLI (npx skillstore add …)
│ └── skillstore/
├── schemas/ # JSON schemas for skill records
├── scripts/ # Maintenance & scoring scripts
└── .github/workflows/ # Submission, audit, and sync automation
The contents of this repo are maintained by Skill Store's automated pipeline. Manual changes are limited to maintainers.
The marketplace catalog is MIT-licensed. Individual skills carry their own licenses — check each skill's LICENSE file.
name: prompting
description: Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.Context engineering = Curating optimal set of tokens during LLM inference
Primary Goal: Find smallest possible set of high-signal tokens that maximize desired outcomes
Use clear semantic sections:
✅ Good: "Validate input before processing" ❌ Bad: "You should always make sure to validate..."
✅ Good: "Use calculate_tax tool with amount and jurisdiction" ❌ Bad: "You might want to consider using..."
✅ Good: Bulleted constraints ❌ Bad: Paragraph of requirements
Don't load full data dumps - use references and load when needed
Persist important info outside context window
Delegate subtasks to specialized agents with minimal context
❌ Verbose explanations ❌ Historical context dumping ❌ Overlapping tool definitions ❌ Premature information loading ❌ Vague instructions ("might", "could", "should")
For full standards: read ${PAI_DIR}/skills/prompting/CLAUDE.md
Anthropic's "Effective Context Engineering for AI Agents"
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