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Agent Skill · 待分类

brainstorm-okrs(头脑风暴 OKRS)

brainstorm-okrs 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

brainstorm-okrs 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为权限未标注;许可证信息还不明确,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 2,446。

总安装 1,582周安装 64GitHub Stars 103下载 497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:brainstorm-okrs(头脑风暴 OKRS)
来源仓库:https://github.com/borghei/claude-skills
仓库路径:skills/brainstorm-okrs
安装命令:
npx skills add https://github.com/borghei/claude-skills --skill brainstorm-okrs
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/borghei/claude-skills --skill brainstorm-okrs

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。

基于 Radical Focus 方法论生成目标与关键结果(OKR),确保聚焦核心价值。输出可衡量的关键结果与反指标检验机制,提升目标质量。适用于季度战略对齐与跨部门协同规划场景。需严格限定单一主题,避免分散精力至多个非核心方向。brainstorm-okrs 属于待分类类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/brainstorm-okrs

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/borghei/claude-skills --skill brainstorm-okrs;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

    权限没有明确标注,第一次使用时只给一个无关紧要的任务,观察它到底读了哪些文件和网络。

常见问题

6 条

brainstorm-okrs 怎么安装?

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

brainstorm-okrs 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。

brainstorm-okrs 需要什么权限?

权限级别没有明确标注。第一次使用时建议只给无关紧要的任务,观察它实际读写了哪些内容。

brainstorm-okrs 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。

brainstorm-okrs 用的人多吗?

公开数据是累计安装 1,582 次,近一周安装 64 次,下载 497 次,GitHub 103 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。

brainstorm-okrs 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

  • 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
brainstorm-okrs

头脑风暴 OKRS · 本页

1,582103权限未标注未明确通过

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

OKR Brainstorming Expert

The agent generates and validates outcome-focused OKR sets using Christina Wodtke's Radical Focus methodology. It produces inspirational objectives with measurable key results, applies counter-metric tests, and scores quality against proven criteria.

Workflow

1. Identify the Theme

The agent asks: "What is the single most important thing this team needs to change this quarter?" The answer becomes the theme. Every OKR must connect back to this theme.

Validation checkpoint: If the user provides more than one theme, the agent pushes back. One theme per team per quarter. Multiple themes means no focus.

2. Generate 3 Distinct OKR Sets

For each set, the agent produces:

  1. Objective -- One qualitative, inspirational statement (no numbers)
  2. Key Result 1 -- Primary metric proving progress
  3. Key Result 2 -- Secondary metric capturing a different dimension
  4. Key Result 3 -- Counter-metric preventing gaming of KR1 and KR2
  5. Rationale -- 2-3 sentences on why this set matters and how it connects to the theme

Objective quality criteria:

  • Qualitative (numbers belong in key results)
  • Inspirational (team would be excited to achieve it)
  • Time-bound (achievable within one quarter)
  • Actionable (team can directly influence the outcome)

Key result quality criteria:

  • Measurable (has a metric with a number)
  • Outcome-focused (measures results, not activities)
  • Set at 60-70% confidence (not sandbagging, not demoralizing)
  • Limited to 3 per objective

3. Apply the Counter-Metric Test

For every pair of key results, the agent asks: "Could we hit these numbers by doing something harmful?" If yes, it adds a counter-metric.

Example: If KR1 is "Increase sign-ups by 40%", a counter-metric is "Maintain activation rate above 60%." Without it, the team could game KR1 by lowering sign-up barriers so far that unqualified users flood in.

4. Validate with Tool

python scripts/okr_validator.py --input okrs.json

The validator scores each OKR set and surfaces quality issues: disguised tasks, missing metrics, output-framed key results, or missing counter-metrics.

Validation checkpoint: Any OKR set scoring below 70% must be revised before committing.

Example: Quarterly OKR Generation

Input: Theme is "retention" for a SaaS product team.

Output:

OKR Set 1:
  Objective: "Become the product teams can't imagine leaving"
  KR1: Reduce monthly churn from 4.2% to 2.5%
  KR2: Increase 90-day retention cohort from 68% to 82%
  KR3 (counter): Maintain NPS score above 45 (prevent forced lock-in tactics)
  Rationale: Churn is the top revenue leak. Improving retention directly
  increases LTV and reduces pressure on acquisition spend.

OKR Set 2:
  Objective: "Make our onboarding so good that users hit value in their first session"
  KR1: Increase Day-1 activation rate from 34% to 55%
  KR2: Reduce time-to-first-value from 12 minutes to under 4 minutes
  KR3 (counter): Maintain support ticket volume below 200/week (don't hide complexity)
  Rationale: Users who activate on Day 1 retain at 3x the rate. Onboarding
  is the highest-leverage retention lever.

OKR Set 3:
  Objective: "Turn our power users into vocal advocates"
  KR1: Increase referral-sourced signups from 8% to 20% of new users
  KR2: Grow active community members from 500 to 2,000
  KR3 (counter): Maintain power user retention above 95% (don't distract them)
  Rationale: Advocacy compounds. Referred users have 37% higher retention
  than paid-acquisition users.
$ python scripts/okr_validator.py --input okrs.json

OKR Validation Results
======================
Set 1: 92/100 - PASS
  Objective: Qualitative, inspirational, time-bound
  KR1: Measurable, outcome-focused, stretch target
  KR2: Measurable, different dimension from KR1
  KR3: Valid counter-metric for churn reduction

Set 2: 88/100 - PASS
  Objective: Qualitative, inspirational, time-bound
  KR1: Measurable, outcome-focused
  KR2: Measurable, tracks different dimension
  KR3: Valid counter-metric
  Note: "under 4 minutes" - verify baseline measurement exists

Set 3: 85/100 - PASS
  Objective: Qualitative, inspirational
  KR1: Measurable, outcome-focused
  KR2: Measurable, but "active" needs precise definition
  KR3: Valid counter-metric

Common OKR Mistakes

MistakeExampleFix
Disguised task"Launch the mobile app"Ask "why?" -- measure the outcome the launch enables
Too many OKRs5 objectives per teamPick 1, maybe 2. More means no focus
100% confidenceTarget you know you will hitStretch to 60-70% confidence
Activity metric"Publish 12 blog posts"Measure impact: "Increase organic traffic by 30%"
Set and forgetReview only at quarter endWeekly check-ins with confidence scoring
Top-down onlyAll OKRs from leadershipCombine top-down direction with bottom-up team insight

OKRs vs KPIs vs North Star Metric

ConceptPurposeCadenceExample
North Star MetricSingle metric capturing core value deliveryPermanentWeekly active users completing a workflow
KPIsHealth indicators across the businessOngoingRevenue, churn rate, response time
OKRsAmbitious quarterly goals that move KPIsQuarterly"Become the fastest onboarding in our category"

Relationship: OKRs are the lever pulled to move KPIs toward the North Star Metric. KPIs indicate business health. The NSM indicates core value delivery. OKRs define what changes this quarter.

Tools

ToolPurposeCommand
okr_validator.pyValidate and score OKR setspython scripts/okr_validator.py --input okrs.json
okr_validator.pyRun demo validationpython scripts/okr_validator.py --demo

Troubleshooting

SymptomLikely CauseResolution
OKR set scores below 70% consistentlyKey results framed as tasks/outputs instead of outcomes, or objective contains numbersAsk "So what?" for each KR until you reach a measurable outcome; remove numbers from objectives
Validator flags "output-oriented language"KR description starts with verbs like "launch", "build", "implement", "ship"Reframe: "Launch mobile app" becomes "Increase mobile-originated revenue from 0% to 15%"
Team sets 5+ objectives per quarterLack of strategic focus or inability to say noEnforce 1 theme per team per quarter; use the Radical Focus constraint: one objective, maybe two
Key results hit 100% every quarterTargets are sandbagged at 100% confidenceStretch to 60-70% confidence; if you hit every KR, you are not being ambitious enough
Counter-metrics missing from OKR setsTeam did not apply the gaming test to KR pairsFor every pair of KRs, ask: "Could we hit these numbers by doing something harmful?" Add a counter-metric if yes
OKRs set and forgotten until quarter endNo weekly check-in rhythm establishedImplement weekly confidence scoring (red/yellow/green) per KR; teams with weekly check-ins complete 43% more goals
Validator rejects input JSONSchema mismatch: missing okr_sets key or key_results array per setEnsure JSON has okr_sets array, each with objective string and key_results array containing description, metric, target_value, current_value

Success Criteria

  • Each OKR set scores above 80/100 on the validator before committing to the quarter
  • Maximum 1-2 objectives per team per quarter (focus over breadth)
  • Every objective is qualitative and inspirational (no numbers in the objective itself)
  • Each objective has exactly 3 key results: primary metric, secondary dimension, and counter-metric
  • Key results are set at 60-70% confidence (stretch, not sandbagged)
  • Weekly confidence check-ins are conducted, not just end-of-quarter reviews
  • OKR retrospectives run at quarter end with structured review of what was learned

Scope & Limitations

In Scope:

  • OKR brainstorming using Christina Wodtke's Radical Focus methodology
  • Generating 3 distinct OKR sets per theme with counter-metric testing
  • Automated validation and scoring of OKR quality (output detection, metric presence, structural checks)
  • Guidance on OKR vs. KPI vs. North Star Metric distinctions
  • Common OKR mistake identification and remediation

Out of Scope:

  • OKR tracking and progress monitoring over the quarter (use dedicated OKR platforms)
  • Company-level OKR cascade and alignment across teams (see senior-pm/ for portfolio alignment)
  • Individual performance-linked OKRs (OKRs should be team goals, not performance reviews)
  • Metric instrumentation or analytics setup for measuring key results

Important Caveats:

  • OKRs work best when combined with weekly check-ins. Teams that review OKRs only at quarter end see 30-45% lower completion rates.
  • The validator catches structural issues but cannot assess strategic quality. A perfectly scored OKR can still be the wrong goal.
  • OKRs should be aligned top-down (strategic direction) and bottom-up (team insight). Pure top-down OKRs reduce team ownership.

Integration Points

IntegrationDirectionDescription
scrum-master/Receives fromSprint velocity and capacity data inform realistic KR target-setting
senior-pm/Receives fromPortfolio strategic priorities shape quarterly OKR themes
execution/outcome-roadmap/Feeds intoOKR key results become success metrics for roadmap Now/Next items
execution/prioritization-frameworks/ComplementsPrioritized initiatives inform which OKR theme to focus on
discovery/identify-assumptions/Receives fromValidated assumptions increase confidence in OKR target feasibility
discovery/brainstorm-experiments/Feeds intoExperiment metrics may become OKR key results when validated

Tool Reference

okr_validator.py

Validates and scores OKR sets against quality criteria. Checks objectives for qualitative/inspirational language, key results for measurable outcomes, and structural completeness.

FlagTypeDefaultDescription
--inputstring(required, mutually exclusive with --demo)Path to JSON file containing OKR sets
--demoflagoffRun validation on built-in demo data (mix of good and bad OKRs)
--formatchoicetextOutput format: text or json

Input JSON schema:

{
  "okr_sets": [
    {
      "objective": "string (qualitative, no numbers)",
      "key_results": [
        {
          "description": "string",
          "metric": "string (unit of measurement)",
          "target_value": "number",
          "current_value": "number (baseline)"
        }
      ]
    }
  ]
}

References

  • references/okr-best-practices.md -- Detailed OKR guide with examples and anti-patterns
  • assets/okr_template.md -- OKR document template and quarterly review format

平台分布

Codex

36.67%
按下载量换算182

Claude

31.23%
按下载量换算155

Cursor

18.95%
按下载量换算94

Gemini CLI

9.12%
按下载量换算45

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限未标注

当前来源未能明确判断权限范围,默认进入异常复核队列。

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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