Token导航 LogoToken导航TokenDH.com
研究检索external-servicegithub未标认证来源可访问许可证需确认审计通过

ultraworkultrawork 搜索

Agent Skill

ultrawork 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

1,259

周安装

53

GitHub Stars

26,798

下载量

441
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:ultrawork(ultrawork 搜索)
来源仓库:https://github.com/yeachan-heo/oh-my-codex
仓库路径:skills/ultrawork
安装命令:
npx skills add https://github.com/yeachan-heo/oh-my-codex --skill ultrawork
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/yeachan-heo/oh-my-codex --skill ultrawork

简介

ultrawork 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用该技能。
  • 安装前需确认权限范围和维护状态,注意可能触发联网、命令执行或文件读写操作。
  • ultrawork 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

<Use_When>

  • Multiple independent tasks can run simultaneously
  • User says "ulw", "ultrawork", or explicitly wants parallel execution
  • Task benefits from concurrent execution plus lightweight evidence before wrap-up
  • You need a direct-tool lane plus optional background evidence lanes without entering Ralph </Use_When>

<Do_Not_Use_When>

  • Task requires guaranteed completion with persistence, architect verification, or deslop/reverification -- use ralph instead (Ralph includes ultrawork)
  • Task requires a full autonomous pipeline -- use autopilot instead (autopilot includes Ralph which includes ultrawork)
  • There is only one sequential task with no parallelism opportunity -- execute directly or delegate to a single executor
  • The request is still in plan-consensus mode -- keep planning artifacts in ralplan until execution is explicitly authorized
  • User needs session persistence for resume -- use ralph, which adds persistence on top of ultrawork </Do_Not_Use_When>

<Why_This_Exists> Sequential task execution wastes time when tasks are independent. Ultrawork keeps the execution branch fast while tightening the protocol: gather enough context first, define pass/fail acceptance criteria before editing, decide deliberately between local execution and delegation, and finish with evidence rather than vibes. </Why_This_Exists>

<Execution_Policy>

  • Gather enough context before implementation. Start with the task intent, desired outcome, constraints, likely touchpoints, and any uncertainty that would change the execution path.
  • If uncertainty is still material after a quick repo read, do a focused evidence pass first instead of immediately editing.
  • Define pass/fail acceptance criteria before launching execution lanes. Include the command, artifact, or manual check that will prove success.
  • Prefer direct tool work when the task is small, coupled, or blocked on immediate local context. Delegate only when the work is independent enough to benefit from parallel execution.
  • When useful, run a direct-tool lane and one or more background evidence lanes at the same time. Evidence lanes can cover docs, tests, regression mapping, or bounded repo analysis.
  • Fire independent agent calls simultaneously -- never serialize independent work.
  • Always pass the model parameter explicitly when delegating.
  • Read docs/shared/agent-tiers.md before first delegation for agent selection guidance.
  • Auto-delegate researcher when official docs, version-aware framework guidance, best practices, or external dependency behavior materially affect task correctness; treat it as an evidence lane, not a replacement primary workflow.
  • Use run_in_background: true for operations over ~30 seconds (installs, builds, tests).
  • Run quick commands (git status, file reads, simple checks) in the foreground.
  • Apply the shared workflow guidance pattern: concise, evidence-dense progress and completion reporting (including speculative/blocked lanes), local overrides for the active workflow branch, and continuation of clear safe execution branches instead of restarting or re-asking.
  • If the user says continue, continue the active workflow branch rather than restarting discovery or re-asking settled questions. </Execution_Policy>

<Tool_Usage>

  • Use LOW-tier delegation for simple lookups and bounded evidence gathering.
  • Use STANDARD-tier delegation for standard implementation and regression work.
  • Use THOROUGH-tier delegation for complex analysis, architectural review, or risky multi-file changes.
  • Prefer a direct-tool lane when the immediate next step is blocked on local context.
  • Prefer background evidence lanes when you can learn something useful in parallel with implementation.
  • Use run_in_background: true for package installs, builds, and test suites.
  • Use foreground execution for quick status checks and file operations. </Tool_Usage>

State Management

Use omx_state MCP tools for ultrawork lifecycle state.

  • On start: state_write({mode: "ultrawork", active: true, reinforcement_count: 1, started_at: "<now>"})
  • On each reinforcement/loop step: state_write({mode: "ultrawork", reinforcement_count: <current>})
  • On completion: state_write({mode: "ultrawork", active: false})
  • On cancellation/cleanup: run $cancel (which should call state_clear(mode="ultrawork"))

Direct-tool lane:

  • update skills/ultrawork/SKILL.md

Background evidence lane:

  • delegate(role="test-engineer", tier="STANDARD", task="Map which hook tests cover ultrawork activation messaging", model="...")
Why good: Context is grounded first, acceptance criteria are explicit, and the direct-tool lane runs alongside a bounded evidence lane.
</Good>

<Good>
Correct use of self-vs-delegate judgment:

Shared-file edit in progress across src/scripts/codex-native-hook.ts and its test -> keep implementation local. Independent regression mapping for keyword-detector coverage -> delegate to a test-engineer lane.

Why good: Shared-file work stays local; independent evidence work fans out.
</Good>

<Bad>
Parallelizing before the task is grounded:

delegate(role="executor", tier="STANDARD", task="Implement whatever seems necessary", model="...") delegate(role="test-engineer", tier="STANDARD", task="Figure out how to test it later", model="...")

Why bad: No context snapshot, no pass/fail target, and delegation starts before the work is shaped.
</Bad>

<Bad>
Claiming success without evidence or manual QA:

Made the changes. Ultrawork should be updated now.

Why bad: No verification output, no acceptance evidence, and no manual QA note when the behavior is user-visible.
</Bad>
</Examples>

<Escalation_And_Stop_Conditions>
- When ultrawork is invoked directly (not via Ralph), apply lightweight verification only -- build/typecheck passes when relevant, affected tests pass, and manual QA notes are captured when needed.
- Ralph owns persistence, architect verification, deslop, and the full verified-completion promise. Do not claim those guarantees from direct ultrawork alone.
- If a task fails repeatedly across retries, report the issue rather than retrying indefinitely.
- Escalate to the user when tasks have unclear dependencies, conflicting requirements, or a materially branching acceptance target.
</Escalation_And_Stop_Conditions>

<Final_Checklist>
- [ ] Task intent and constraints were grounded before editing
- [ ] Pass/fail acceptance criteria were stated before execution
- [ ] Parallel lanes were used only for independent work
- [ ] Build/typecheck passes when relevant
- [ ] Affected tests pass
- [ ] Manual QA notes recorded when behavior is user-visible
- [ ] No new errors introduced
- [ ] Completion claim stays inside ultrawork's lightweight-verification boundary
</Final_Checklist>

<Advanced>
## Relationship to Other Modes

ralph (persistence + verified completion wrapper) -- includes: ultrawork (this skill) -- provides: high-throughput execution + lightweight evidence

autopilot (autonomous execution) -- includes: ralph -- includes: ultrawork (this skill)

ecomode (token efficiency) -- modifies: ultrawork's model selection

Ultrawork is the parallelism and execution-discipline layer. Ralph adds persistence, architect verification, deslop, and retry-until-done behavior. Autopilot adds the broader autonomous lifecycle pipeline. Ecomode adjusts ultrawork's model routing to favor cheaper models.
</Advanced>

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

32.85%
按下载量换算145

Claude

32.31%
按下载量换算142

Cursor

21.04%
按下载量换算93

Gemini CLI

8.87%
按下载量换算39

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

继续浏览同类 Skills