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skill-optimization技能优化

Agent Skill

skill-optimization 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

198

周安装

8

GitHub Stars

191

下载量

62
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:skill-optimization(技能优化)
来源仓库:https://github.com/shinpr/ai-coding-project-boilerplate
仓库路径:skills/skill-optimization
安装命令:
npx skills add https://github.com/shinpr/ai-coding-project-boilerplate --skill skill-optimization
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/shinpr/ai-coding-project-boilerplate --skill skill-optimization

简介

skill-optimization 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。
  • 安装方式:github,使用 npx skills add 命令添加。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Skill Content Optimization

Core Philosophy

  1. Evidence-Based: Grounded in prompt engineering research, applied to skill authoring
  2. Concrete: Each pattern provides detection criteria and transform methods
  3. Structure-Focused: Optimizes expression and organization; domain knowledge remains unchanged

Content Optimization Patterns

P1: Critical (Must Fix)

Issues that directly reduce LLM execution accuracy when consuming the skill.

BP-001: Negative Instructions → Positive Form

DetectionTransform
"don't", "do not", "never", "avoid" in skill instructionsReframe as positive directive with equivalent constraint

Skill example:

  • Before: "Don't use generic variable names"
  • After: "Use descriptive variable names that reflect purpose (e.g., userId not x)"

Why critical for skills: LLM attention mechanisms focus on negated content. Skill instructions with "don't" increase probability of the forbidden behavior.

BP-002: Vague Instructions → Specific Criteria

DetectionTransform
"appropriate", "good", "proper", "best", "should be clear"Replace with measurable if-then criteria or concrete thresholds
Missing output format, scope, or success criteriaAdd explicit constraints

Skill example:

  • Before: "Handle errors appropriately"
  • After: "Error handling criteria: 1. try-catch for external API calls, file I/O, JSON.parse 2. Log: error.name, error.stack, timestamp 3. Re-throw with context if caller needs to handle"

Why critical for skills: Accounts for ~40% of execution variance. Every vague instruction forces LLM to guess.

BP-003: Missing Output Format → Structured Output

DetectionTransform
Skill describes what to do but not the expected deliverable formatAdd output section with structure, fields, and example

Skill example:

  • Before: "Analyze the code for issues"
  • After: "Output format: ## Issues Found with table: | Severity | Location | Description | Suggested Fix |"

Why critical for skills: Structured output constraints reduce hallucination and make skill results consistent.

P2: High Impact (Should Fix)

Issues that reduce skill effectiveness when addressed.

BP-004: Unstructured Content → Organized Format

DetectionTransform
Wall of text without headingsApply standard section order (see below)
Multiple topics mixed in one sectionSplit into distinct headed sections
No tables for reference dataConvert lists of criteria/patterns to tables

Standard skill section order:

  1. Context/Prerequisites
  2. Core concepts (definitions, patterns)
  3. Process/Methodology (step-by-step)
  4. Output format/Examples
  5. Quality checklist
  6. References

Conditional: Skip restructuring if skill is under 30 lines and covers a single topic.

BP-005: Missing Context → Explicit Prerequisites

DetectionTransform
Skill assumes knowledge not statedAdd Prerequisites section listing required context
Domain terms used without definitionAdd definitions inline or in a glossary table
No "when to use" guidanceAdd trigger conditions with concrete scenarios

Skill example:

  • Before: "Apply the strangler pattern for migration"
  • After: "Prerequisite: Existing monolith with identifiable module boundaries. When to use: Replacing legacy module while maintaining production traffic."

BP-006: Complex Content → Decomposed Steps

DetectionTransform
3+ objectives in one instructionBreak into numbered steps with checkpoints
Sequential dependencies not explicitAdd dependency markers between steps
No intermediate verificationInsert checkpoint after each step

Conditional: Skip decomposition for simple reference tables or single-criteria rules.

Key insight: Goal is evaluable granularity with quality checkpoints, not decomposition for its own sake.

P3: Enhancement (Could Fix)

Incremental improvements for specific contexts.

BP-007: Biased Examples → Diverse Coverage

DetectionTransform
All examples share same pattern/structureAdd edge cases and exceptions
Only happy-path examplesAdd error cases, boundary conditions
Examples all same complexityInclude simple, moderate, and complex

BP-008: No Uncertainty Permission → Explicit Escalation

DetectionTransform
Skill demands definitive answers alwaysAdd escalation criteria for ambiguous cases
No "when to stop" guidanceAdd explicit stopping conditions

Skill example:

  • Before: "Determine the root cause"
  • After: "Determine the root cause. If root cause is uncertain after 3 investigation cycles, report top 3 hypotheses with confidence levels and evidence for each."

9 Skill Editing Principles

Measurable quality criteria for skill content. Each principle includes a pass/fail test.

#PrinciplePass CriteriaFail Example
1Context efficiencyEvery sentence contributes to LLM decision-making. No filler."This is an important skill that helps with..."
2DeduplicationNo concept explained twice within the skill or across skillsSame error handling rules in both coding-standards and typescript-rules
3GroupingRelated criteria in single section (minimize read operations)Scattered error handling rules across 4 sections
4MeasurabilityAll criteria use if-then format or concrete thresholds"Write clean code" without definition of clean
5Positive formInstructions state what to do (BP-001 applied)"Don't use any" instead of "Use only X"
6Consistent notationUniform heading levels, list styles, table formatsMix of -, *, 1. in same context
7Explicit prerequisitesAll assumed knowledge statedUses "DI" without defining Dependency Injection
8Priority orderingMost important items first, exceptions lastEdge cases before common patterns
9Scope boundariesExplicit coverage: what this skill addresses vs references to other skillsOverlapping guidance with no cross-reference

References

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

35.24%
按下载量换算22

Claude

28.54%
按下载量换算18

Cursor

18.91%
按下载量换算12

Gemini CLI

9.73%
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

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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