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Agent Skill · 研究检索

optimize-skills(优化技能)

optimize-skills 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。

optimize-skills 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 73,543。

总安装 1周安装 12GitHub Stars 2下载 97核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:optimize-skills(优化技能)
来源仓库:https://github.com/ahgraber/skills
仓库路径:skills/optimize-skills
安装命令:
npx skills add https://github.com/ahgraber/skills --skill optimize-skills
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/ahgraber/skills --skill optimize-skills

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。适用于关键词搜索、任务场景匹配和来源线索筛选等研究检索场景。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。安装前需确认权限范围、维护状态及是否触发联网或文件操作。

optimize-skills 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/optimize-skills

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ahgraber/skills --skill optimize-skills;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

optimize-skills 怎么安装?

在终端执行 npx skills add https://github.com/ahgraber/skills --skill optimize-skills。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

optimize-skills 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

optimize-skills 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

optimize-skills 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

optimize-skills 用的人多吗?

公开数据是累计安装 1 次,近一周安装 12 次,下载 97 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

optimize-skills 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
optimize-skills

优化技能 · 本页

12只读未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Optimizing Skills

Use this skill to create, review, or improve SKILL.md-based skills so they trigger correctly, stay concise, and execute reliably.

Invocation Notice

  • Inform the user when this skill is being invoked by name: optimize-skills.

When to Use

  • Creating a new reusable skill from repeated work patterns.
  • Updating an existing skill that under-triggers, over-triggers, or misfires.
  • Tightening a skill that is too long, redundant, or hard to execute.
  • Converting narrative guidance into concise, imperative instructions.
  • Rebalancing where content should live across SKILL.md, references/, assets/, and scripts/.

Overview

What is a Skill?

A skill is a reference guide for proven techniques, patterns, or tools, typically classed as procedural knowledge or best practices. Skills help future Agent instances find and apply effective approaches.

Skills are: Reusable techniques, patterns, tools, reference guides

Skills are NOT: Narratives about how you solved a problem once

When to Create a Skill

Create when:

  • Technique wasn't intuitively obvious to you or required multiple iterations to get right.
  • You'd reference this again across projects / Others would benefit from knowing this.
  • Pattern applies broadly (not project-specific)
  • Triggerable by specific user intents or common failure modes.

Don't create for:

  • One-off solutions
  • Standard practices well-documented elsewhere
  • Project-specific conventions that aren't broadly applicable

Workflow

Phase 1: Preparation

  1. Choose the path:

- New skill: initialize scaffold and baseline structure. - Existing skill: load current SKILL.md and related resources as baseline.

  1. Define the target workflow first:

- List the execution steps in order, including prerequisites, gates, and outputs. - Keep steps imperative and executable.

  1. Determine trigger scenarios in working notes:

- Capture 2-3 scenarios that must trigger the skill. - Capture up to 2 scenarios that must not trigger the skill.

  1. Decide whether a flowchart is required:

- Use markdown-only workflow when flow is linear and obvious. - Add a small DOT flowchart only when branching/loops are non-obvious.

Phase 2: Draft

  1. Draft metadata and usage guidance from preparation:

- Keep frontmatter to name and description. - Encode trigger scenarios in description and ## When to Use (and ## When Not to Use when helpful).

  1. Draft the skill body in imperative form:

- Keep instructions short, specific, and ordered by execution. - Move deep detail to references/, assets/, or scripts/ and link from SKILL.md.

Phase 3: Review and Optimize

  1. Run scenario and functional checks against realistic prompts.
  2. Review resource fit:

- Confirm references/assets/scripts are sufficient and scoped. - Offload verbose SKILL.md sections into resources where appropriate.

  1. Optimize the draft:

- Tighten triggering (under/over-triggering). - Remove redundancy and improve progressive disclosure. - Re-check whether flowchart usage is still justified.

  1. Iterate until trigger behavior and execution quality both pass.

Core Principles

  • Optimize for triggering: description must emphasize when to use the skill (references/skills-search-optimization.md).
  • Treat trigger scenarios as authoring scaffolding; the final skill should expose triggers through description and ## When to Use.
  • Keep frontmatter metadata small (about 100 tokens combined).
  • Keep main SKILL.md under 500 lines and focused on action.
  • Use progressive disclosure: metadata -> SKILL.md -> references/scripts/assets.
  • Choose the right degree of freedom: text, pseudocode, or scripts depending on fragility.
  • Prefer reusable resources (scripts, templates) over repeated prose.

Progressive Disclosure Targets

  • Metadata (name + description): small startup footprint, ideally ~100 tokens.
  • SKILL.md: keep actionable and concise, target <5000 tokens and <500 lines.
  • scripts/, references/, assets/: loaded only when needed; keep files narrow so agents pull less context.

Flowchart Guidance

digraph when_flowchart {
    "Need to show process guidance?" [shape=diamond];
    "Non-obvious decision or loop?" [shape=diamond];
    "Use markdown (list/table/code)" [shape=box];
    "Use small inline DOT flowchart" [shape=box];

    "Need to show process guidance?" -> "Non-obvious decision or loop?" [label="yes"];
    "Need to show process guidance?" -> "Use markdown (list/table/code)" [label="no"];
    "Non-obvious decision or loop?" -> "Use small inline DOT flowchart" [label="yes"];
    "Non-obvious decision or loop?" -> "Use markdown (list/table/code)" [label="no"];
}
  • Use markdown lists/tables/code blocks by default.
  • Add DOT only when decision logic or loops are easy to misapply.
  • Avoid placeholder node labels; use concrete actions and conditions.
  • Follow references/graphviz-conventions.dot for node shapes and labels.
  • Keep flowcharts small and trigger-based; split large flows into focused subgraphs.

Render DOT to SVG with scripts/render-dot.py. Output SVGs are written to the target skill's assets/ directory.

scripts/render-dot.py skills/optimize-skills/references/skill-workflow.dot
scripts/render-dot.py skills/optimize-skills/SKILL.md
scripts/render-dot.py skills/optimize-skills/SKILL.md --force # overwrite existing SVGs

Output

SKILL.md Structure

skills/
  skill-name/
    SKILL.md      # Main reference (required)
    assets/       # (optional) Static reusable resources such as templates or figures
    references/   # (optional) On-demand documentation, organized by topic or variant
    scripts/      # (optional) Executable helpers for deterministic tasks;
                  # scripts should be self-contained or clearly declare dependencies,
                  # include clear errors, and handle edge cases.

Rules

  • SKILL.md must be named exactly SKILL.md.
  • Folder name must be kebab-case, matching the name in frontmatter.
  • Do not add README.md inside the skill.
  • YAML frontmatter must include name and description fields.
  • name must be kebab-case and match the folder name.
  • description should emphasize when to use the skill and include triggers/symptoms.
  • Avoid workflow summaries in the description.
  • Keep descriptions short and specific.
  • Prefer ## When to Use / ## When Not to Use for trigger cues; do not add a dedicated trigger-scenarios section unless explicitly requested by the repo.
  • Refer to assets/skill-template.md for a suggested (but easily modified) template structure.

Common Mistakes

  • Summarizing workflow in description instead of stating actionable triggers and symptoms.
  • Copying working trigger scenarios directly into the final skill instead of converting them into description and ## When to Use.
  • Keeping workflows as one giant graph instead of splitting into trigger-based subgraphs.
  • Repeating deep reference material in SKILL.md instead of linking to references/.
  • Leaving scripts implicit: deterministic steps should be executable where possible.

References

  • assets/skill-template.md for a suggested SKILL.md structure.
  • references/best-practices.md: checklists, structure guidance, testing, and troubleshooting patterns.
  • references/skills-search-optimization.md: description and trigger optimization rules.
  • references/skill-workflow.dot: canonical workflow for this skill.
  • references/graphviz-conventions.dot: DOT style and semantics for workflow diagrams.

平台分布

Codex

36.77%
按下载量换算36

Claude

27.87%
按下载量换算27

Cursor

17.06%
按下载量换算17

Gemini CLI

9.69%
按下载量换算9

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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