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Ck:Problem Solving

Community
manhvann
ck:problem-solving

Apply systematic problem-solving techniques when stuck. Use for complexity spirals, innovation blocks, recurring patterns, assumption constraints, simplification cascades, scale uncertainty.

Overview

Publishermanhvann
Repositorycodexkit
Skill nameck:problem-solving
Stars
88
Forks
81
Bundled files
7
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.

  • 7 bundled files

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

  • Open source

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

Installation

Install the Ck:Problem Solving 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/manhvann/codexkit/tree/main/.agents/skills/problem-solving
  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/manhvann/codexkit.git /tmp/codexkit
mkdir -p .claude/skills
cp -r /tmp/codexkit/.agents/skills/problem-solving .claude/skills/manhvann-ck-problem-solving
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ck:Problem Solving 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 Ck:Problem Solving 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 Ck:Problem Solving 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.

Problem-Solving Techniques

Systematic approaches for different types of stuck-ness. Each technique targets specific problem patterns.

When to Use

Apply when encountering:

  • Complexity spiraling - Multiple implementations, growing special cases, excessive branching
  • Innovation blocks - Conventional solutions inadequate, need breakthrough thinking
  • Recurring patterns - Same issue across domains, reinventing solutions
  • Assumption constraints - Forced into "only way", can't question premise
  • Scale uncertainty - Production readiness unclear, edge cases unknown
  • General stuck-ness - Unsure which technique applies

Quick Dispatch

Match symptom to technique:

Stuck SymptomTechniqueReference
Same thing implemented 5+ ways, growing special casesSimplification Cascadesreferences/simplification-cascades.md
Conventional solutions inadequate, need breakthroughCollision-Zone Thinkingreferences/collision-zone-thinking.md
Same issue in different places, reinventing wheelsMeta-Pattern Recognitionreferences/meta-pattern-recognition.md
Solution feels forced, "must be done this way"Inversion Exercisereferences/inversion-exercise.md
Will this work at production? Edge cases unclear?Scale Gamereferences/scale-game.md
Unsure which technique to useWhen Stuckreferences/when-stuck.md

Core Techniques

1. Simplification Cascades

Find one insight eliminating multiple components. "If this is true, we don't need X, Y, Z."

Key insight: Everything is a special case of one general pattern.

Red flag: "Just need to add one more case..." (repeating forever)

2. Collision-Zone Thinking

Force unrelated concepts together to discover emergent properties. "What if we treated X like Y?"

Key insight: Revolutionary ideas from deliberate metaphor-mixing.

Red flag: "I've tried everything in this domain"

3. Meta-Pattern Recognition

Spot patterns appearing in 3+ domains to find universal principles.

Key insight: Patterns in how patterns emerge reveal reusable abstractions.

Red flag: "This problem is unique" (probably not)

4. Inversion Exercise

Flip core assumptions to reveal hidden constraints. "What if the opposite were true?"

Key insight: Valid inversions reveal context-dependence of "rules."

Red flag: "There's only one way to do this"

5. Scale Game

Test at extremes (1000x bigger/smaller, instant/year-long) to expose fundamental truths.

Key insight: What works at one scale fails at another.

Red flag: "Should scale fine" (without testing)

Application Process

  1. Identify stuck-type - Match symptom to technique above
  2. Load detailed reference - Read specific technique from references/
  3. Apply systematically - Follow technique's process
  4. Document insights - Record what worked/failed
  5. Combine if needed - Some problems need multiple techniques

Combining Techniques

Powerful combinations:

  • Simplification + Meta-pattern - Find pattern, then simplify all instances
  • Collision + Inversion - Force metaphor, then invert its assumptions
  • Scale + Simplification - Extremes reveal what to eliminate
  • Meta-pattern + Scale - Universal patterns tested at extremes

References

Load detailed guides as needed:

  • references/when-stuck.md - Dispatch flowchart and decision tree
  • references/simplification-cascades.md - Cascade detection and extraction
  • references/collision-zone-thinking.md - Metaphor collision process
  • references/meta-pattern-recognition.md - Pattern abstraction techniques
  • references/inversion-exercise.md - Assumption flipping methodology
  • references/scale-game.md - Extreme testing procedures
  • references/attribution.md - Source and adaptation notes

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 Ck:Problem Solving AI skill do?

Apply systematic problem-solving techniques when stuck. Use for complexity spirals, innovation blocks, recurring patterns, assumption constraints, simplification cascades, scale uncertainty.

Why use Ck:Problem Solving on TypingMind?

Because you install it once and use it with any model. Ck:Problem Solving 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 Ck:Problem Solving in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/manhvann/codexkit/tree/main/.agents/skills/problem-solving. 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 Ck:Problem Solving?

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 Ck:Problem Solving?

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

Is the Ck:Problem Solving AI skill free?

Yes. It is published on GitHub by manhvann 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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