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Vc Sequential Thinking

CommunityPopular
withkynam
vc-sequential-thinking

Apply step-by-step analysis for complex problems with revision capability. Use for multi-step reasoning, hypothesis verification, adaptive planning, problem decomposition, course correction.

Overview

Publisherwithkynam
Repositoryvibecode-pro-max-kit
Skill namevc-sequential-thinking
Stars
1.1K
Forks
234
Bundled files
11
LicenseMIT
Links
Skill sourceRepository
  • 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.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Vc Sequential Thinking 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.
    https://github.com/withkynam/vibecode-pro-max-kit/tree/main/.claude/skills/vc-sequential-thinking
  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/withkynam/vibecode-pro-max-kit.git /tmp/vibecode-pro-max-kit
mkdir -p .claude/skills
cp -r /tmp/vibecode-pro-max-kit/.claude/skills/vc-sequential-thinking .claude/skills/vc-sequential-thinking
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vc Sequential Thinking 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 Vc Sequential Thinking 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 Vc Sequential Thinking 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.

Sequential Thinking

Output style: Follow process/development-protocols/communication-standards.md — answer-first, plain language, no unexplained jargon, TL;DR on long responses.

Structured problem-solving via manageable, reflective thought sequences with dynamic adjustment.

When to Apply

  • Complex problem decomposition
  • Adaptive planning with revision capability
  • Analysis needing course correction
  • Problems with unclear/emerging scope
  • Multi-step solutions requiring context maintenance
  • Hypothesis-driven investigation/debugging

Core Process

1. Start with Loose Estimate

Thought 1/5: [Initial analysis]

Adjust dynamically as understanding evolves.

2. Structure Each Thought

  • Build on previous context explicitly
  • Address one aspect per thought
  • State assumptions, uncertainties, realizations
  • Signal what next thought should address

3. Apply Dynamic Adjustment

  • Expand: More complexity discovered → increase total
  • Contract: Simpler than expected → decrease total
  • Revise: New insight invalidates previous → mark revision
  • Branch: Multiple approaches → explore alternatives

4. Use Revision When Needed

Thought 5/8 [REVISION of Thought 2]: [Corrected understanding]
- Original: [What was stated]
- Why revised: [New insight]
- Impact: [What changes]

5. Branch for Alternatives

Thought 4/7 [BRANCH A from Thought 2]: [Approach A]
Thought 4/7 [BRANCH B from Thought 2]: [Approach B]

Compare explicitly, converge with decision rationale.

6. Generate & Verify Hypotheses

Thought 6/9 [HYPOTHESIS]: [Proposed solution]
Thought 7/9 [VERIFICATION]: [Test results]

Iterate until hypothesis verified.

7. Complete Only When Ready

Mark final: Thought N/N [FINAL]

Complete when:

  • Solution verified
  • All critical aspects addressed
  • Confidence achieved
  • No outstanding uncertainties

Application Modes

Explicit: Use visible thought markers when complexity warrants visible reasoning or user requests breakdown.

Implicit: Apply methodology internally for routine problem-solving where thinking aids accuracy without cluttering response.

Scripts (Optional)

Optional scripts for deterministic validation/tracking:

  • scripts/process-thought.js - Validate & track thoughts with history
  • scripts/format-thought.js - Format for display (box/markdown/simple)

See README.md for usage examples. Use when validation/persistence needed; otherwise apply methodology directly.

References

Load when deeper understanding needed:

  • references/core-patterns.md - Revision & branching patterns
  • references/examples-api.md - API design example
  • references/examples-debug.md - Debugging example
  • references/examples-architecture.md - Architecture decision example
  • references/advanced-techniques.md - Spiral refinement, hypothesis testing, convergence
  • references/advanced-strategies.md - Uncertainty, revision cascades, meta-thinking

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Vc Sequential Thinking AI skill do?

Apply step-by-step analysis for complex problems with revision capability. Use for multi-step reasoning, hypothesis verification, adaptive planning, problem decomposition, course correction.

Why use Vc Sequential Thinking on TypingMind?

Because you install it once and use it with any model. Vc Sequential Thinking 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 Vc Sequential Thinking in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/withkynam/vibecode-pro-max-kit/tree/main/.claude/skills/vc-sequential-thinking. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Vc Sequential Thinking?

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 Vc Sequential Thinking?

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

Is the Vc Sequential Thinking AI skill free?

Yes. It is published on GitHub by withkynam 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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