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Thinking Second Order

CommunityPopular
tjboudreaux
thinking-second-order

When a change has effects past the immediate fix—incentives, scale, feedback—trace consequence chains with timing and probability before committing.

Overview

Publishertjboudreaux
Repositorycc-thinking-skills
Skill namethinking-second-order
Stars
1.3K
Forks
158
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by tjboudreaux on GitHub. Read the source before you install it.

Installation

Install the Thinking Second Order AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/tjboudreaux/cc-thinking-skills.git /tmp/cc-thinking-skills
mkdir -p .claude/skills
cp -r /tmp/cc-thinking-skills/skills/thinking-second-order .claude/skills/thinking-second-order
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Thinking Second Order in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Thinking Second Order on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Thinking Second Order is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Second-Order Consequence Chains

Do not stop at the intended first effect. Trace what happens next across actors, time, and feedback until the chain stops changing the decision.

When to Use

  • Strategic, policy, incentive, or architecture choices with lasting coupling.
  • The obvious fix feels too easy or has known backfire patterns.
  • Success or scale would create new problems (load, gaming, debt).
  • Need to compare options by delayed effects, not only day-one benefit.

When NOT to Use

  • Local reversible edit with no incentive or cross-component coupling—just ship and observe.
  • Full system structure (stocks, many loops, leverage ranking) is the goal—use systems.
  • Pre-mortem of failure modes for a plan already chosen—use pre-mortem.
  • Pure mechanical changes (rename, format) with no behavioral effect.

Procedure

  1. State decision and first-order effect. One sentence each: action and intended immediate result.
  2. Chain "and then what?" At least two further orders. For each link record: effect, who responds, rough probability (high/med/low), timing (immediate / next cycle / at scale), and whether it feeds back into the original problem (reinforce or counteract).
  3. Expand affected parties. Who else reacts (users, operators, other teams, attackers, markets)? What incentives does the change create or destroy?
  4. Scale test. Ask what happens if everyone does this or usage grows 10x. Mark paths that only appear under scale or repetition.
  5. Prune and decide. Drop speculative links that do not change the choice. Keep only effects that alter go/no-go, design, or mitigations. Revise the action or add guards where second-order harm exceeds first-order gain.

Stop when further "and then what?" no longer changes the decision, or the remaining chain is pure speculation without mechanism.

Output

text
decision: <action>
first_order: <intended immediate effect>
chain:
  - order: 2
    effect: <what>
    actors: <who>
    p: high|med|low
    when: immediate|next_cycle|at_scale
    feedback: none|reinforce|balance
  - order: 3
    ...
scale_if_universal: <one sentence or n/a>
revised_decision: <same | modified action | no-go>
mitigations: <guards for kept risks>

Verification

  • Falsify: If no credible second-order path changes the choice, first-order is enough—stop inventing cascades. If the core issue is multi-loop structure rather than one decision's trail, switch to systems.
  • Stop: End at the first order that no longer affects the decision; do not pad to a fixed depth.
  • Over-application guard: No low-probability sci-fi chains. No treating parameter tweaks as deep strategy. Probability and timing required on kept links; omit decoration without mechanism.

Frequently asked questions

What does the Thinking Second Order AI skill do?

When a change has effects past the immediate fix—incentives, scale, feedback—trace consequence chains with timing and probability before committing.

Why use Thinking Second Order on TypingMind?

Because you install it once and use it with any model. Thinking Second Order is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Thinking Second Order in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tjboudreaux/cc-thinking-skills/tree/main/skills/thinking-second-order. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Thinking Second Order?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Thinking Second Order?

As many as you like. As long as a model supports skills, you can use Thinking Second Order with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Thinking Second Order AI skill free?

Yes. It is published on GitHub by tjboudreaux under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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