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Agent Skill · 待分类

send-to-linear(send TO Linear 工具)

用于处理 Linear 项目、Issue、团队、周期和产品开发任务流。它适合让 Agent 辅助查询任务状态、整理需求队列、创建缺陷或汇总迭代进展。使用时需要确认 workspace、team、label、assignee 和状态流转规则;涉及批量创建或修改任务时,应先核对字段和目标团队,避免把草稿需求直接写入正式项目。

send-to-linear 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在待分类类的 11,209 个 Skill 里排第 1,343。

总安装 3,816周安装 159GitHub Stars 11下载 1,272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:send-to-linear(send TO Linear 工具)
来源仓库:https://github.com/casper-studios/casper-marketplace
仓库路径:skills/send-to-linear
安装命令:
npx skills add https://github.com/casper-studios/casper-marketplace --skill send-to-linear
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/casper-studios/casper-marketplace --skill send-to-linear

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

send-to-linear 用于处理 Linear 平台上的项目、Issue 和任务流。它可辅助查询任务状态、创建缺陷或汇总迭代进展,提升产品管理效率。通过 npx skills add 命令安装,需确保 workspace 和团队字段配置正确。

使用时请核对 assignee、label 和状态流转规则,避免将草稿直接写入正式项目。建议在批量操作前先小范围测试,确认字段映射无误后再扩展使用。

来源仓库内路径:skills/send-to-linear

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/casper-studios/casper-marketplace --skill send…;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

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

send-to-linear 怎么安装?

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

send-to-linear 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。

send-to-linear 需要什么权限?

权限级别是调用外部服务。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。

send-to-linear 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。

send-to-linear 用的人多吗?

公开数据是累计安装 3,816 次,近一周安装 159 次,下载 1,272 次,GitHub 11 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。

send-to-linear 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。

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。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

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。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
send-to-linear

send TO Linear 工具 · 本页

3,81611调用外部服务未明确有提醒

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

Send to Linear

Turn unstructured input into well-structured Linear tickets.

Setup

Config resolution

Look for team configuration in this order (first match wins):

  1. ~/.agents/configs/send-to-linear/config.json (user overrides)
  2. references/config.json (bundled defaults, relative to this skill file)

Use the user config if found. Otherwise fall back to the bundled config.json.

If no user config exists AND the bundled config has empty required fields (team, default_assignee), stop and prompt the user:

No local config found. The bundled references/config.json has empty defaults and will be overwritten whenever this skill updates. Create a user config at: ~/.agents/configs/send-to-linear/config.json Copy the bundled references/config.json as a starting point and fill in your team, project, assignee, labels, and conventions.

Template resolution

Same pattern for the ticket template:

  1. ~/.agents/configs/send-to-linear/ticket-template.md (user overrides)
  2. references/ticket-template.md (bundled default)

The template rarely needs customization, so no prompt if only the bundled version exists.

Phase 1: Ingest Input

Accept any combination of:

  • Slack dump — pasted messages or fetched via Slack MCP tools
  • Call transcript — from Fireflies (mcp__fireflies__* tools), pasted text, or a file
  • Screenshots — read image files with the Read tool
  • Meeting notes / docs — any markdown, text, or document content
  • User description — freeform "we need X, Y, Z"

If the user's input is ambiguous or incomplete, ask one clarifying question before proceeding. Do not over-interrogate.

For Fireflies transcripts specifically: fetch both the summary (fireflies_get_summary) and full transcript (fireflies_get_transcript). Use the summary for topic identification, the full transcript for detail extraction.

Phase 2: Extract Topics and Actionable Items

For short input (<5K chars): extract directly in the main context.

For long input (>5K chars, e.g. full call transcripts): launch parallel subagents, one per major topic or time segment, to extract:

  1. Concrete examples and use cases — the most critical output. Capture specific scenarios, companies/tickers, KPIs, exact quotes, timestamps, and reasoning chains. A ticket saying "fix interpretation errors" is useless. A ticket saying "fix interpretation errors — e.g., when commentary says 'flat to down' for Intel CapEx but consensus expects 'down', recognize this as upward revision" is actionable.
  2. Feature requirements — what needs to be built or changed
  3. Limitations/boundaries — things explicitly ruled out
  4. Acceptance criteria — testable conditions

Categorize items as:

  • Actionable tickets — clear scope, can be worked on immediately
  • Ideas / needs more thought — visionary or exploratory, tracked but not immediately actionable

Phase 3: Draft Tickets to Scratchpad

Write to .claude/scratchpad/linear-tickets-YYYY-MM-DD.md using the format from references/ticket-template.md.

Every ticket with a real-world example from the source MUST include that example verbatim — do not summarize away specifics.

Phase 4: Verification (for long-form input only)

Skip for short/simple input. For call transcripts or long Slack threads:

Launch a verification subagent that reads the full source material and the drafted tickets, then produces a gap list:

  • Use cases mentioned but missing from tickets
  • Action items assigned to people but not captured
  • Design decisions agreed upon but not in acceptance criteria
  • Any "we need to do X" statements not in any ticket

Update the draft with any gaps found.

Phase 5: User Review

STOP. Tell the user the file is ready and wait for explicit instruction before creating anything in Linear.

The user may restructure, merge, split, rename, add notes, or tell you to skip items. Apply all feedback to the scratchpad file before proceeding.

Phase 6: Create in Linear (only on explicit approval)

Read config using the resolution order from Setup, then:

  1. mcp__linear__list_teams — resolve team ID
  2. mcp__linear__list_issue_labels — resolve label IDs
  3. mcp__linear__list_projects — resolve project ID (if configured)
  4. mcp__linear__list_cycles with type: "current" — resolve current cycle (if assign_to_current_cycle is true)

Create each approved ticket with mcp__linear__create_issue:

  • team: from config
  • project: from config
  • assignee: from config
  • cycle: current cycle number
  • state: from config default_status
  • labels: matched from ticket's Labels field
  • title: from ticket
  • description: full ticket body in markdown
  • links: source link if available (e.g. Fireflies transcript URL, Slack permalink)

Report created ticket identifiers back to the user.

Key Rules

  1. Concrete examples are non-negotiable. Engineers understand what to build from specific scenarios, not abstract descriptions. Preserve full reasoning chains, exact quotes, and real-world context.
  2. Never create tickets without user approval. Always draft to scratchpad first.
  3. Config is defaults, not constraints. User can override team, assignee, labels, or any other field per invocation.
  4. Don't over-consolidate. If two items are independent work, they're separate tickets. Group only when items are truly part of the same deliverable.
  5. Standalone requirements buried in conversation are tickets too. Things said in passing like "we also need to compare dates" represent distinct work items.

平台分布

Codex

37.54%
按下载量换算478

Claude

29.59%
按下载量换算376

Cursor

19.37%
按下载量换算246

Gemini CLI

10.41%
按下载量换算132

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

调用外部服务

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。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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