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Agent Skill · 研究检索

running-flow(运行流程)

running-flow 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。

running-flow 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,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 63,254。

总安装 318周安装 13GitHub Stars 1下载 103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:running-flow(运行流程)
来源仓库:https://github.com/robomotionio/agent-skills
仓库路径:skills/running-flow
安装命令:
npx skills add https://github.com/robomotionio/agent-skills --skill running-flow
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/robomotionio/agent-skills --skill running-flow

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。适合根据关键词或任务场景快速定位候选结果。可结合来源仓库和安装命令进一步核验用法。建议确认权限范围及是否会触发联网或文件读写。

running-flow 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/running-flow

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/robomotionio/agent-skills --skill running-flow;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

    它需要接触敏感数据,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

running-flow 怎么安装?

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

running-flow 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。

running-flow 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

running-flow 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。

running-flow 用的人多吗?

公开数据是累计安装 318 次,近一周安装 13 次,下载 103 次,GitHub 1 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。

running-flow 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
running-flow

运行流程 · 本页

3181接触敏感数据未明确通过

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

Running a Robomotion Flow

Run a flow on a robot, watch the agent-mode event stream, react to failures. Four moving parts:

  1. Pre-flight — robomotion validate <flow-dir> catches pspec/schema errors locally in <1s before you ever submit. Cheap; always do it first.
  2. Robot process — robomotion-deskbot connect keeps the robot online. One long-lived process.
  3. Trigger — robomotion run <flow-dir> builds locally, submits, and streams the event log.
  4. Observation — run tails the JSONL session log; events are bracketed by {"event":"agent_mode","status":"start"} … {"event":"agent_mode","status":"end"}.

Step 1 — Validate (mandatory pre-flight)

robomotion validate <flow-dir>           # exit 0 = pspec-clean, 1 = errors on stderr

Catches every "wrong property name", "non-existent node type", "invalid port" before any robot-side work. The CLI rebuilds + validates without touching *.designer.ts or emitting JSON. Don't skip it — diagnosing a pspec error from a node_error event in the run log is much slower than reading the validate output.

If validate fails: read stderr, fix main.ts, re-run validate. Loop until exit 0, then proceed.

robomotion run also validates as part of its build step, so a bad flow won't reach the robot — but you'll find out *after* the network round-trip and Submitting flow for execution... spinner. Validate first.

Step 2 — Robot must be connected

The robot must be connected BEFORE robomotion run can schedule anything on it. Usually a long-lived session in a separate terminal:

robomotion-deskbot connect -i "$ROBOMOTION_USER_EMAIL" -w demo.robomotion.io -r Extremis

Flags: -i identity (email), -w workspace domain, -r robot name/id, --token to skip password prompt. See robomotion-deskbot connect --help.

No log-tee setup needed — robomotion run reads the session log file the deskbot writes to ~/.config/robomotion/agent/logs/sessions/<studio_id>.jsonl.

Step 3 — Trigger the run

export ROBOMOTION_API_KEY=<your-api-key>
export ROBOMOTION_USER_EMAIL=<your-email>

robomotion run <flow-dir>                          # interactive robot picker
robomotion run <flow-dir> --robot <robot-id>       # scripted
robomotion run                                     # defaults to main.ts in cwd

The CLI accepts either a flow directory (resolves to main.ts inside) or a .ts file. It:

  1. Builds the flow (validates against pspec; fails fast on errors).
  2. Picks a robot (or uses --robot).
  3. POST /v1/flows.agent.run with a fresh studio_id (printed on success).

Prereqs: Step 1 (validate) clean; ROBOMOTION_API_KEY set; the target robot online (Step 2).

Step 4 — Observe the agent event stream

robomotion run follows the stream by default — it tails a session log file the deskbot writes at:

~/.config/robomotion/agent/logs/sessions/<studio_id>.jsonl           (Linux/macOS)
%LOCALAPPDATA%\Robomotion\agent\logs\sessions\<studio_id>.jsonl      (Windows)

Events are compact one-line JSON, terminated by agent_mode:end. Example:

{"event":"agent_mode","status":"start"}
{"event":"flow_start","flow":"Imported Write To Clipboard","version":"local"}
{"event":"node_start","node":"Start"}
{"event":"node_end","node":"Start","duration_ms":21}
{"event":"node_start","node":"Get Clipboard Data"}
{"event":"node_end","node":"Get Clipboard Data","duration_ms":4780}
{"event":"flow_end","status":"success","duration_ms":8852}
{"event":"agent_mode","status":"end"}

Exit codes from robomotion run:

CodeMeaning
0flow_end status=success
1flow_end status=error or flow_error
2Tail timeout (session still running) — raise --timeout or re-read the log file
3Session submitted but log file never appeared — robot is on a different machine so its log lives there. The run still proceeds on the robot; check the Flow Designer for progress.

Flags: --no-follow (fire-and-forget, no stream), --log-wait <s> (how long to wait for the file to appear, default 5), --timeout <s> (overall follow budget, default 300).

Event reference

EventFieldsMeaning
agent_mode`status: "start" \"end"`Brackets the run. end is a safety-net terminal event.
flow_startflow, versionFlow started.
flow_end`status: "success" \"error", duration_ms, error?`Flow finished — primary terminal event.
flow_errorerror, node?, node_id?, duration_msUnhandled flow-level error.
node_startnodeNode entered.
node_endnode, duration_msNode completed.
node_errornode, error, duration_msNode threw — your signal to fix.
lognode?, level, msgCore.Flow.Log output.
debugnode, msgCore.Programming.Debug payload (truncated to 255 bytes per field).
connectedmsgRobot registered with the workspace.
ready—Robot ready to accept commands.

Re-reading after the run

robomotion run consumes the log while streaming. The file persists afterwards; re-read it with any JSONL tool:

jq . ~/.config/robomotion/agent/logs/sessions/<studio_id>.jsonl

Step 5 — The validate → run → observe → fix loop

Target autonomous iteration (bounded retries; stop on user request):

  1. Validate locally: robomotion validate <flow-dir> — must exit 0 before submitting. If non-zero, fix main.ts from the stderr report and repeat this step (do NOT submit a known-broken flow).
  2. Submit: robomotion run <flow-dir> --robot <id> — capture the Session / Studio ID.
  3. Stream: run tails the agent log automatically until agent_mode:end.
  4. Classify:

- flow_end status=success (CLI exit 0) → report and stop. - node_error or flow_error (CLI exit 1) → inspect error + node, fix main.ts, back to step 1. Max 3 retries without user confirmation. - Timeout (CLI exit 2) → flow may still be running on the robot; report and ask. - Log unreachable (CLI exit 3) → robot is remote; watch progress in the Flow Designer instead.

  1. Between retries, keep mock/test fixtures stable so a passing run actually proves the fix.

Common node_error patterns

error fragmentLikely causeFix
Cannot read property 'X' of undefinedUpstream node didn't set msg.XCheck the writing node's out* property; verify Message('X') upstream.
Network timeout / ETIMEDOUTURL unreachable from robotConfirm URL, raise timeout, check proxy.
element not found / selector failureStale selectorRe-run exploring-browser and update inSelector.
property not found in pspecInvalid property namerobomotion describe node <type> to verify the schema.
Vault has to be selectedMissing optCredentials on Core.Vault.GetItemAdd optCredentials: Credential({vaultId, itemId}).

Other useful CLI verbs

  • robomotion get robots — list available robots (same data the interactive picker uses).
  • robomotion stop --robot <robot-id> — stop whatever flow is running on a robot.
  • robomotion get vaults / robomotion get vault-items <vault-id> — credentials available to your workspace.

Quick errors and fixes

MessageCauseFix
ROBOMOTION_API_KEY environment variable is requiredEnv var missingexport ROBOMOTION_API_KEY=<key>
No main.ts found in directory: <path>Wrong dir or missing main.tsPoint at a directory that contains main.ts.
Flow validation failedpspec violation at build timeFix errors (use validating-flow for a detailed report) and re-run.
No robots foundNo robots registered in workspaceCreate a robot at https://app.robomotion.io, then robomotion-deskbot connect.
Run submits but no agent_mode:start appearsRobot offline or in another workspaceConfirm connected event in the agent log; match -w and -r on the deskbot.

Related Skills

  • creating-flow — generate the flow
  • validating-flow — schema check (local, no robot needed)
  • testing-flow — behavioral tests with mocks (no robot needed)

平台分布

Codex

36.08%
按下载量换算37

Claude

29.7%
按下载量换算31

Cursor

18.99%
按下载量换算20

Gemini CLI

11.3%
按下载量换算12

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。目前只有一个公开来源,建议同时核对源仓库。

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