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thinking-ooda思考乌达

Agent Skill

thinking-ooda 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。

总安装

541

周安装

23

GitHub Stars

46

下载量

190
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:thinking-ooda(思考乌达)
来源仓库:https://github.com/tjboudreaux/cc-thinking-skills
仓库路径:skills/thinking-ooda
安装命令:
npx skills add https://github.com/tjboudreaux/cc-thinking-skills --skill thinking-ooda
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/tjboudreaux/cc-thinking-skills --skill thinking-ooda

简介

思考乌达用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合敏捷开发中的观察-判断-决策-行动循环管理。
  • 将任务拆解为 OODA 各阶段,提供时间盒划分与反馈收集建议。
  • 安装命令:npx skills add https://github.com/tjboudreaux/cc-thinking-skills --skill thinking-ooda
  • 强调迭代节奏,应与 CI/CD 流程集成以实现自动化阶段切换。

SKILL.md

OODA Loop

Overview

The OODA Loop (Observe, Orient, Decide, Act), developed by military strategist Colonel John Boyd, is a framework for rapid decision-making in dynamic, competitive, or time-sensitive situations. The key insight: speed through the loop creates advantage. In competitive scenarios, operating faster than your opponent disrupts their decision-making.

Core Principle: Agility beats perfection. Cycle through OODA faster than the situation changes (or faster than your opponent).

When to Use

  • Incident response and outages
  • Competitive market situations
  • Time-sensitive decisions
  • Rapidly changing requirements
  • Crisis management
  • Debugging under pressure
  • Any situation requiring quick adaptation

Decision flow:

Situation changing rapidly? → yes → Need quick decisions? → yes → APPLY OODA LOOP
                                                         ↘ no → Standard analysis
                          ↘ no → Deliberate analysis may be better

The Four Phases

1. OBSERVE

Gather information rapidly

What to observe:

  • Current state of the system/situation
  • Changes since last observation
  • External factors and environment
  • Feedback from previous actions
  • Competitor/opponent movements
Incident Example:
- Error rates: Spiking 10x normal
- Affected services: API gateway, user service
- Timeline: Started 5 minutes ago
- Recent changes: Deploy 15 min ago
- User reports: "Can't log in"

Observation principles:

  • Cast wide net initially, narrow as pattern emerges
  • Don't filter prematurely—gather raw data
  • Include lagging AND leading indicators
  • Time-bound: Don't observe forever

2. ORIENT

Make sense of observations

Orientation factors (Boyd's framework):

  • Cultural traditions: How does our org typically respond?
  • Genetic heritage: Our built-in biases and tendencies
  • Previous experience: What have we seen before?
  • New information: What's different this time?
  • Analysis/Synthesis: Combining all of the above
Incident Example:
- Pattern matches: Similar to DB connection pool exhaustion last month
- But different: No DB metrics anomaly this time
- Recent deploy touched: Auth service rate limiting
- Hypothesis: Rate limit config too aggressive

Orient is the CRITICAL phase:

  • This is where mental models apply
  • Misorientation leads to wrong decisions
  • Update orientation as new info arrives
  • Challenge your initial framing

3. DECIDE

Select course of action

Decision characteristics:

  • Based on current orientation
  • Acknowledges uncertainty
  • Identifies what to observe next
  • Has implicit/explicit hypothesis
Incident Example:
Decision: Roll back auth service deploy
Hypothesis: This will restore normal error rates
Observation plan: Watch error rates for 2 minutes post-rollback
Fallback: If no improvement, investigate DB connections

Decision speed vs. quality tradeoff:

  • 70% confidence now beats 90% confidence too late
  • Reversible decisions: Bias toward action
  • Irreversible decisions: Gather more info first
  • "Good enough" decision executed fast > perfect decision too slow

4. ACT

Execute the decision

Action principles:

  • Execute decisively
  • Immediately return to OBSERVE
  • Don't wait for complete results
  • Create new observations through action
Incident Example:
Action: kubectl rollback deployment/auth-service
Immediate observe: Error rates, response times
Time limit: 2 minutes to see effect

The loop restarts:

  • Actions create new situation
  • New situation requires new observation
  • Cycle continues until stable state

OODA Loop Speed

Tempo Advantage

Operating inside opponent's loop:

You:     O → O → D → A → O → O → D → A → O ...
Opponent:     O → O → O →  ...  → D → A (too late)

When you complete loops faster:

  • Your actions change situation before they decide
  • Their orientation becomes outdated
  • They react to old information
  • You maintain initiative

Speed Multipliers

FactorEffect
Pre-planned responsesSkip D phase for known scenarios
Distributed authorityParallel loops at different levels
Clear mental modelsFaster O (orientation)
Training/practiceFaster execution (A)
Good observabilityFaster O (observation)

Speed Killers

FactorEffect
Waiting for certaintyLoop stalls at O or D
Hierarchical approvalAdds latency to D
Information overloadO phase never completes
Analysis paralysisLoop stalls at Orient
Perfect solution seekingD phase never completes

Application Patterns

Incident Response

OBSERVE: Metrics, logs, alerts, user reports
ORIENT:  Match pattern, form hypothesis, assess blast radius
DECIDE:  Mitigation action (rollback, scale, disable)
ACT:     Execute mitigation, immediately observe results
LOOP:    Continue until stable

Competitive Response

OBSERVE: Competitor announcement, market reaction, customer feedback
ORIENT:  Assess threat level, identify our advantages, gaps
DECIDE:  Response strategy (match, differentiate, ignore)
ACT:     Execute response, observe market reaction
LOOP:    Adjust based on effectiveness

Debugging Under Pressure

OBSERVE: Error messages, stack traces, recent changes
ORIENT:  Form hypothesis about cause
DECIDE:  Test most likely hypothesis first
ACT:     Add logging, try fix, or eliminate possibility
LOOP:    Update hypothesis based on results

OODA for Teams

Parallel Loops

Different team members can run loops simultaneously:

SRE:     Infrastructure OODA (scaling, failover)
Dev:     Code OODA (debugging, fixes)
Support: Communication OODA (users, stakeholders)
Lead:    Strategy OODA (coordination, escalation)

Shared Orientation

Teams need synchronized mental models:

  • Runbooks create shared orientation
  • Incident channels share observations
  • Clear roles enable parallel action
  • Post-incident updates orientation for next time

Verification Checklist

  • Observing actual current state, not assumptions
  • Orientation considers multiple hypotheses
  • Decision is actionable and time-bound
  • Action creates observable feedback
  • Loop is actually cycling (not stuck in one phase)
  • Speed is appropriate to situation urgency

Common Failure Modes

FailureSymptomFix
Observation overloadCan't process all dataFilter to key indicators
Orientation lockStuck on one hypothesisForce alternative framing
Decision paralysisWaiting for certaintySet decision deadline
Action without observationBlind executionMandate observe after act
Single loopNot cyclingTime-box each phase

Key Questions

  • "What do I observe RIGHT NOW?" (not 5 minutes ago)
  • "What does this mean? What pattern does it match?"
  • "What's my best action given current understanding?"
  • "How will I know if my action worked?"
  • "Am I cycling fast enough?"

Boyd's Insight

"He who can handle the quickest rate of change survives."

The goal isn't just making decisions—it's making decisions faster than the situation evolves, faster than competitors adapt, faster than problems compound. Speed creates options; delay eliminates them.

适合场景

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02

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能力 2

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能力 3

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能力 4

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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

36.21%
按下载量换算69

Claude

29.87%
按下载量换算57

Cursor

17.26%
按下载量换算33

Gemini CLI

9.89%
按下载量换算19

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

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安装前确认

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