Token导航 LogoToken导航

Agent Skill · 效率

qualify(qualify 效率)

qualify 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 OpenClaw 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

qualify 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 7,204。

总安装 8,372周安装 342GitHub Stars 公开资料未说明下载 2,709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-0
版本
1.0.0

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:qualify(qualify 效率)
来源仓库:https://github.com/agimodel/qualify
安装命令:
openclaw skills install qualify
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install qualify

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

qualify 用于在投入资源前评估潜在客户、项目或机会的资格,避免无效投入。适合在 OpenClaw 中需要围绕仓库状态或协作事项进行整理时使用。通过 clawhub 安装,命令为 openclaw skills install qualify,具体用法参考来源仓库。

安装前需确认权限范围和维护状态,注意可能涉及数据筛选逻辑。建议结合原始文档了解评估维度和输出格式后再使用。

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 OpenClaw;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 openclaw skills install qualify;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

qualify 怎么安装?

在终端执行 openclaw skills install qualify。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

qualify 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

qualify 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。

qualify 是免费的吗?

来源标注的许可证是 MIT-0。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。

qualify 用的人多吗?

公开数据是累计安装 8,372 次,近一周安装 342 次,下载 2,709 次。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。

qualify 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
qualify

qualify 效率 · 本页

8,372—只读MIT-0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

name
qualify
description
>

Qualify

Qualification is the discipline of deciding what deserves pursuit.

Most wasted effort does not come from poor execution. It comes from pursuing the wrong things too far.

People spend time on leads that will not buy, clients they cannot serve well, projects that should never have started, candidates who are not a fit, and requests that create complexity without return.

This skill helps define, apply, and improve qualification logic so effort goes where it matters.

Trigger Conditions

Use this skill when the user needs to:

  • qualify leads before sales effort
  • decide which prospects are worth outreach
  • screen candidates before interviews
  • assess whether a client, project, or request is a fit
  • define go/no-go criteria
  • reduce wasted effort on weak opportunities
  • improve intake or filtering logic
  • separate promising opportunities from distracting noise

Also trigger when the user says things like:

  • "How do I qualify this"
  • "What makes this worth pursuing"
  • "Should we take this client"
  • "How do I screen better"
  • "What criteria should I use"
  • "How do I filter out bad fits"
  • "I need a qualification framework"

Core Principle

Qualification is not about saying no more often.

It is about saying yes more intelligently.

A good qualification system does three things:

  • identifies fit
  • identifies readiness
  • identifies whether the expected return justifies the effort

The goal is not to eliminate uncertainty. The goal is to stop avoidable misallocation.

What This Skill Does

This skill helps:

  • define qualification criteria before effort is invested
  • separate fit, timing, value, and risk
  • create go/no-go logic for opportunities and requests
  • identify disqualifiers early
  • improve screening and filtering systems
  • reduce false positives
  • route better opportunities into deeper workflows

Default Outputs

Depending on the request, produce one or more of the following:

  1. Qualification Framework

A structured set of criteria showing what counts as qualified and why.

  1. Qualification Scorecard

A practical model for comparing opportunities or requests on explicit dimensions.

  1. Go/No-Go Logic

A decision rule for whether something should be pursued, paused, rejected, or escalated.

  1. Disqualifier Map

A list of early warning signs and conditions that should stop pursuit.

  1. Screening Workflow

A stage-by-stage process for filtering items before deeper commitment.

  1. Qualification Audit

A diagnosis of where the current qualification logic is too loose, too rigid, or poorly applied.

Response Rules

When responding:

  • define what is being qualified
  • identify the desired downstream outcome
  • separate fit from timing
  • separate value from urgency
  • identify disqualifiers early
  • make criteria explicit rather than intuitive
  • reduce wasted effort and false positives
  • favor usable judgment over fake precision

Qualification Architecture

~~~python QUALIFICATION_ARCHITECTURE = { "core_elements": { "object": "What is being qualified", "desired_outcome": "What success would look like if pursued", "fit": "How well the item matches the need, offer, or system", "readiness": "Whether now is a viable time to proceed", "value": "Why the item is worth pursuing if successful", "risk": "What may make pursuit costly, unstable, or low quality", "disqualifiers": "Conditions that should stop or delay pursuit" }, "guiding_questions": [ "What are we deciding yes or no to", "What makes this a fit or non-fit", "Is the opportunity real or only theoretical", "What signals readiness or lack of readiness", "What effort would pursuit require", "What would make this low quality even if technically possible" ] } ~~~

Qualification Workflow

~~~python QUALIFICATION_WORKFLOW = { "step_1_define_object": { "purpose": "Clarify what is being screened", "examples": [ "lead", "prospect", "client request", "candidate", "project", "partnership opportunity" ] }, "step_2_define_outcome": { "purpose": "Clarify why qualification matters", "examples": [ "worth a sales call", "worth custom proposal effort", "worth an interview round", "worth onboarding", "worth strategic attention" ] }, "step_3_define_fit_criteria": { "purpose": "Identify stable characteristics that matter", "examples": [ "budget or spending ability", "problem relevance", "scope match", "segment fit", "capability match", "decision-maker alignment" ] }, "step_4_define_readiness_signals": { "purpose": "Identify whether this should be pursued now", "examples": [ "active pain", "timeline pressure", "clear need", "stakeholder engagement", "available resources", "decision timeline" ] }, "step_5_define_disqualifiers": { "purpose": "Prevent avoidable wasted effort", "examples": [ "wrong use case", "misaligned expectations", "no buying authority", "no urgency", "economically weak fit", "delivery risk too high", "history of instability" ] }, "step_6_route_decision": { "purpose": "Turn qualification into action", "destinations": [ "pursue now", "nurture later", "pause", "reject", "escalate for review" ] } } ~~~

Common Qualification Types

~~~python QUALIFICATION_TYPES = { "sales_qualification": { "use_when": "Deciding whether a lead or opportunity deserves sales effort", "focus": ["fit", "need", "budget", "authority", "timing", "conversion likelihood"] }, "client_qualification": { "use_when": "Deciding whether to take on a client or engagement", "focus": ["fit", "scope realism", "expectation alignment", "economics", "delivery risk"] }, "candidate_qualification": { "use_when": "Screening people before deeper recruiting effort", "focus": ["role fit", "motivation", "readiness", "capability", "risk", "practical constraints"] }, "project_qualification": { "use_when": "Deciding whether a project is worth starting or prioritizing", "focus": ["strategic fit", "resource load", "expected return", "dependencies", "execution risk"] }, "request_qualification": { "use_when": "Filtering incoming requests, asks, or opportunities", "focus": ["importance", "fit", "urgency", "cost to fulfill", "tradeoffs"] } } ~~~

Qualification Logic

~~~python QUALIFICATION_LOGIC = { "principles": [ "A possible fit is not the same as a good fit", "Readiness matters as much as relevance", "Disqualifying early preserves capacity", "The cost of a false positive is often underestimated", "Not every good opportunity is a good opportunity now", "Qualification should simplify later decisions, not replace them" ], "common_failures": [ "Pursuing anything that looks interesting", "Confusing politeness or curiosity with intent", "Ignoring economic or delivery reality", "No explicit disqualifiers", "Letting exceptions become the normal standard", "Qualifying too late after custom effort is already spent" ], "corrections": [ "State criteria before evaluating cases", "Separate fit, timing, and value", "Make disqualifiers visible", "Create pause and nurture paths instead of only yes/no", "Tighten screening before expensive effort begins" ] } ~~~

Qualification Output Format

Qualification Summary

  • Object Being Qualified:
  • Desired Outcome:
  • Fit Criteria:
  • Readiness Signals:
  • Value Indicators:
  • Disqualifiers:
  • Decision Paths:
  • Risks or Ambiguities:
  • Recommended Next Step:

Boundaries

This skill helps define qualification logic, screening criteria, and go/no-go decisions.

It does not replace legal, compliance, HR, procurement, medical, financial, or regulatory judgment. For regulated or high-stakes decisions, outputs should be adapted to the user's jurisdiction, industry requirements, and internal approval processes.

Quality Check Before Delivering

  • [ ] The object being qualified is clearly defined
  • [ ] Fit and readiness are separated
  • [ ] Disqualifiers are explicit
  • [ ] Decision paths are actionable
  • [ ] Criteria reduce wasted effort
  • [ ] Output is practical rather than abstract
  • [ ] The next step is concrete

平台分布

OpenClaw

82.95%
按下载量换算2,247

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills