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qualifyqualify 效率

Agent Skill

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。

总安装

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周安装

342

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下载量

2,709
OpenClaw

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

MIT-0

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: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

简介

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。

SKILL.md

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

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

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按下载量换算2,247

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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

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