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Agent Skill · 研究检索

constraints-scheduling(约束调度)

constraints-scheduling 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。

constraints-scheduling 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;许可证为 MIT,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 40,677。

总安装 1,261周安装 51GitHub Stars 93下载 396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
MIT

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:constraints-scheduling(约束调度)
来源仓库:https://github.com/letta-ai/skills
仓库路径:skills/constraints-scheduling
安装命令:
npx skills add https://github.com/letta-ai/skills --skill constraints-scheduling
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/letta-ai/skills --skill constraints-scheduling

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。

约束调度提供系统化方法处理多方时间冲突,找到满足参与者可用性、偏好与日历事件的共同时段。适用于会议安排、课程表编排和资源预约等涉及多重约束的时间管理场景。通过 GitHub 安装并使用 npx skills add 命令添加,强调输入验证与程序化确认流程。

输出结果需经人工复核,特别是在跨时区或存在隐性依赖的情况下需额外小心验证。constraints-scheduling 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/constraints-scheduling

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/letta-ai/skills --skill constraints-scheduling;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

constraints-scheduling 怎么安装?

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

constraints-scheduling 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。

constraints-scheduling 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。

constraints-scheduling 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

constraints-scheduling 用的人多吗?

公开数据是累计安装 1,261 次,近一周安装 51 次,下载 396 次,GitHub 93 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。

constraints-scheduling 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 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

  • 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
constraints-scheduling

约束调度 · 本页

1,26193只读MIT未通过

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

Constraints Scheduling

Overview

This skill provides guidance for solving constraint-based scheduling problems where the goal is to find time slots that satisfy multiple constraints from different sources (participant availability, existing calendars, preferences, etc.). It emphasizes systematic data extraction, programmatic verification, and proper handling of time granularity requirements.

Workflow

Phase 1: Input Verification and Data Extraction

Before any analysis, establish complete and verified data:

  1. Verify input file integrity first - Check that input files have not been modified and contain expected data before processing
  2. Extract complete data - Ensure all file contents are fully read (watch for truncation in tool outputs)
  3. Use appropriate parsers - For structured formats like ICS (iCalendar), use proper parsing libraries rather than manual text extraction
  4. Document extracted data - Create a clear summary of all extracted events, constraints, and preferences

Phase 2: Constraint Classification

Organize constraints into clear categories before searching for solutions:

  1. Hard constraints (must be satisfied):

- Participant availability windows - Existing calendar conflicts - Required meeting duration - Non-negotiable time restrictions

  1. Soft constraints (preferences for tie-breaking):

- Preferred days of week - Preferred times of day - Buffer time preferences - Other stated preferences

  1. Edge case constraints:

- Boundary conditions (e.g., meeting ending exactly when lunch begins) - Day-specific rules (e.g., early departure on certain days) - Buffer requirements (e.g., no meetings after a certain time)

Phase 3: Systematic Solution Search

Implement a comprehensive search approach:

  1. Respect stated granularity - If the task specifies minute-level granularity, check all possible start times at that granularity (not just hour boundaries)
  2. Use programmatic verification - Write a script that encodes all constraints and systematically checks every possible time slot
  3. Single comprehensive script - Avoid duplicating work between manual analysis and code; trust programmatic verification
  4. Check earliest valid slot - When finding the "earliest" slot, ensure the search starts from the correct baseline and respects granularity

Phase 4: Verification

Before finalizing the solution:

  1. Verify against all hard constraints - Explicitly check each constraint against the selected time
  2. Document boundary conditions - For edge cases (meeting ending exactly at a constraint boundary), explicitly confirm validity
  3. Cross-reference with source data - Ensure the selected slot doesn't conflict with any extracted calendar events
  4. Verify output format - Ensure the output matches any specified format requirements

Common Pitfalls

Data Extraction Issues

  • Truncated file reads - Tool outputs may truncate long files; always verify complete data extraction or use programmatic parsing
  • Manual parsing errors - Avoid manually extracting structured data (like ICS events) when libraries exist
  • Missing events - Incomplete calendar parsing can lead to scheduling conflicts

Granularity Mistakes

  • Ignoring stated granularity - If minute-level granularity is required, checking only hourly slots may miss valid earlier times
  • Boundary assumptions - A meeting at 10:00-11:00 and a constraint starting at 11:00 may or may not conflict depending on requirements

Analysis Disorganization

  • Redundant manual analysis - Performing the same constraint checks manually multiple times wastes effort and introduces inconsistency
  • Stream-of-consciousness reasoning - Jumping between days and constraints without structure increases error risk
  • Late verification - Checking input integrity after analysis is complete, rather than before

Constraint Handling

  • Treating soft constraints as hard - Preferences should be tie-breakers, not elimination criteria
  • Missing edge cases - Day-specific rules, buffer requirements, and boundary conditions are easily overlooked
  • Incomplete constraint enumeration - Failing to extract all constraints from input data

Verification Checklist

Before submitting a scheduling solution, verify:

  • All input files were read completely without truncation
  • Input file integrity was verified (not modified)
  • All hard constraints are satisfied by the selected time
  • No conflicts exist with any extracted calendar events
  • Stated granularity requirements were respected in the search
  • Edge cases and boundary conditions were explicitly checked
  • Soft constraints were used appropriately for selection among valid options
  • Output format matches requirements

Best Practices

  1. Start with programmatic approach - Immediately write a comprehensive script to parse inputs and check constraints rather than manual analysis
  2. Use proper libraries - For ICS files, use icalendar or similar libraries; for other structured formats, use appropriate parsers
  3. Structure analysis hierarchically - Organize by constraint category rather than jumping between different days or time slots
  4. Single source of truth - Trust programmatic verification; avoid duplicating analysis manually
  5. Explicit boundary handling - Document how boundary conditions are handled (inclusive vs exclusive endpoints)
  6. Complete search - When finding "earliest" or "best" slots, search all possibilities at the required granularity

平台分布

Claude Code

30.09%
按下载量换算119

Gemini CLI

24.02%
按下载量换算95

Codex

17.69%
按下载量换算70

Antigravity

13.87%
按下载量换算55

OpenCode

8.2%
按下载量换算32

windsurf

3.64%
按下载量换算14

安全审计

Gen Agent Trust Hub

未通过

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。

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