thinking-ooda

thinking-ooda is a skill for Claude Code from tjboudreaux/cc-thinking-skills. It costs 41 tokens per session (681 once invoked), scanned A, original, MIT.

A decision method called the OODA loop: Observe, Orient, Decide, and Act, then repeat as conditions change.

In plain words
What is it for?
Use it for outages, intermittent failures, changing live systems, and other time-limited decisions where the next action can be safely adjusted.
Why use it?
It helps during incidents or debugging when waiting for complete certainty would make the situation worse. It encourages quick, reversible actions followed by fresh observations.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Part of the cc-thinking-skills plugin — 28 skills shipped together

Good fit Use it for outages, intermittent failures, changing live systems, and other time-limited decisions where the next action can be safely adjusted.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tjboudreaux/cc-thinking-skills/thinking-ooda
About the project

Claude Code Thinking Skills is a catalogue of 28 portable skills that give coding agents structured procedures for reasoning about decisions, diagnosis, risk, strategy, and related problems. It is intended for Claude Code, GitHub Copilot, Codex, Cursor, and other tools that support Agent Skills.

tjboudreaux/cc-thinking-skills · 1,300 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add tjboudreaux/cc-thinking-skills --skill thinking-ooda
Clone the repo
git clone --depth 1 https://github.com/tjboudreaux/cc-thinking-skills

Made for: Claude Code.

Or install cc-thinking-skills, the plugin that ships this one along with the rest of its 28 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for thinking-ooda

README.md
[![agentmods](https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-ooda/github.svg)](https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-ooda)
Your own site
<a href="https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-ooda"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-ooda/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for thinking-ooda

Your own site · 80×15
<a href="https://agentmods.dev/skills/tjboudreaux/cc-thinking-skills/thinking-ooda"><img src="https://agentmods.dev/badge/skills/tjboudreaux/cc-thinking-skills/thinking-ooda.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 681 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 12 Mar 2026
  • Snyk pass 12 Mar 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00041 $0.00681
Opus 5 $0.00020 $0.00341
Sonnet 5 $0.00008 $0.00136
Haiku 4.5 $0.00004 $0.00068

Measured 11d ago against content hash b5120a4734a5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

thinking-ooda scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/thinking-ooda/SKILL.md · 47 lines

How it starts

The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OODA Loop

Core rule: For reversible moves under time pressure, act on ~70% confidence, then immediately re-observe. Cycle faster than the situation compounds; a late perfect plan loses to a fast loop.

When to Use

  • Incident response, outage, or ongoing degradation where state is still moving.
  • Debugging a moving target (intermittent failure, live traffic shift).
  • Any time-bounded decision where waiting for full certainty costs more than a reversible action.

When NOT to Use

  • The situation is static and you have time — deliberate analysis or a hypothesis differential wins.
  • The next action is irreversible or high blast-radius — raise the evidence bar; 70% is not enough.
  • You can cheaply localize the cause (read the failing diff, log, or metric) — test that hypothesis directly instead of looping in the dark.
  • There is no time pressure and no changing environment — OODA adds churn without value.

Procedure

  1. Observe (time-boxed): gather the cheapest high-signal state now — metrics, logs, alerts, recent deploys/config, and feedback from the last action. Cap the window; do not collect forever.
  2. Orient: match observations to a pattern and form ≥2 candidate explanations. Update or discard the mental model when data contradicts it; refuse single-hypothesis lock.
  3. Decide: pick one reversible action that tests the leading hypothesis. State confidence (~70% threshold for reversible moves), the predicted effect, the observation you will check next, and a time box for that check.
  4. Act: execute once, decisively, with a known rollback or degrade path.
  5. Re-observe immediately: compare outcome to prediction within the time box; feed the result into the next Observe. Loop until stable or until the next move is no longer reversible enough for this skill.
  6. Stop condition: exit the loop when the system is stable, the remaining work is static analysis, or the next step requires irreversible commitment — then switch method.

Read the full file on GitHub · 47 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 47 lines · 41 tokens per session scan A b5120a4734a5

Subscribe to this mod's changes

thinking-ooda is a skill published in the GitHub repository tjboudreaux/cc-thinking-skills (1,300 stars, last pushed 1mo ago), licensed MIT. It adds 41 tokens to every session and 681 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

forensic-read

Read any document the way a detective reads a witness statement — surface what it is NOT saying. Unlike a summarizer (which tells you what a text says), this skill exposes the subtext: hedging and weasel words, conspicuous omissions, buried leads, frequency tells, tone shifts, and non-answers. Use it on earnings…

3243dwon/clear-eye · 170 tokens

pre-mortem

Find what will kill a plan before it's committed to — by assuming it already failed and working backwards to the causes. Based on Gary Klein's pre-mortem technique. Unlike generic "what are the risks?" brainstorming, this skill imagines a specific, vivid failure six months out, reasons back to the most likely causes…

3243dwon/clear-eye · 162 tokens

second-order

Reason past the obvious, first-order consequence to the second-, third-, and long-tail effects everyone else stops short of. Where most analysis says "X causes Y", this skill asks "and then what?" — mapping the cascade, surfacing the non-obvious winners and losers, the reflexive responses, and the effects that only…

3243dwon/clear-eye · 157 tokens

Vizra ADK Memory System

Implement persistent memory, session context, and vector memory (RAG) for AI agents.

vizra-ai/vizra-adk · 24 tokens

foundation-models

On-device LLM integration using Apple's Foundation Models framework. Use when implementing AI text generation, structured output, or tool calling.

rshankras/claude-code-apple-skills · 29 tokens

analytics-interpretation

Interpret app metrics and make data-driven decisions. Covers DAU/MAU, retention, LTV, ARPU, App Store Connect analytics, AARRR funnel analysis, cohort analysis, and diagnostic decision trees. Use when user wants to understand their metrics, diagnose problems, or build a data-driven growth plan.

rshankras/claude-code-apple-skills · 68 tokens