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@35ffd55
by shingo imotasimota/agent-skills85 stars
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Refracting thinking by challenging assumptions, combining cross-domain knowledge, and shifting perspectives to reframe problems. Use for stuck situations or paradigm shifts. Does not write code.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/flux

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referencedomain-classifier.md

≈1.7k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Domain Classifier

Purpose: Cynefin-based problem classification and automatic framework selection. Read when: You are in the CLASSIFY phase and need to determine which frameworks to apply.


Contents

  • Cynefin Framework Overview
  • Domain Classification Criteria
  • Framework Selection Matrix
  • Classification Procedure
  • Edge Cases

Cynefin Framework Overview

The Cynefin framework (Dave Snowden, 1999) classifies problems into domains based on the relationship between cause and effect.

┌──────────────────┬──────────────────┐
│    Complex        │   Complicated     │
│  因果は事後判明     │   因果は分析で判明   │
│  Probe→Sense→    │   Sense→Analyze→  │
│  Respond          │   Respond         │
├──────────────────┼──────────────────┤
│    Chaotic        │   Clear           │
│  因果関係なし       │   因果関係明確      │
│  Act→Sense→      │   Sense→          │
│  Respond          │   Categorize→     │
│                   │   Respond         │
└──────────────────┴──────────────────┘
          ┌──────────┐
          │ Confused  │
          │ (未分類)   │
          └──────────┘

Domain Classification Criteria

Clear (明確)

Characteristics:

  • Cause and effect are obvious to everyone.
  • Best practices exist and are well-documented.
  • The problem has been solved many times before.
  • Constraints are known and stable.

Signals in user input:

  • "We know the solution but need a better version"
  • "Standard approach isn't working well enough"
  • "How do we optimize X?"

Response pattern: Sense → Categorize → Respond


Complicated (煩雑)

Characteristics:

  • Cause and effect discoverable through analysis.
  • Expert knowledge required to understand relationships.
  • Multiple valid approaches exist.
  • Good practices (not best practices) apply.

Signals in user input:

  • "We have options but can't decide which is best"
  • "The experts disagree on the approach"
  • "We need to analyze before deciding"

Response pattern: Sense → Analyze → Respond


Complex (複雑)

Characteristics:

  • Cause and effect only understood in retrospect.
  • Emergent behavior — outcomes are unpredictable.
  • Multiple interacting agents/systems.
  • The problem changes as you try to solve it.

Signals in user input:

  • "We keep solving the wrong problem"
  • "Every fix creates new problems"
  • "We don't know what we don't know"
  • "Stakeholders can't agree on what the problem even is"

Response pattern: Probe → Sense → Respond


Chaotic (混沌)

Characteristics:

  • No perceivable cause and effect relationship.
  • High turbulence, novel situation.
  • Need to act first to create stability.
  • No time for analysis.

Signals in user input:

  • "Everything is falling apart"
  • "Nothing we try works"
  • "This is completely unprecedented"
  • "We need to do something, anything"

Response pattern: Act → Sense → Respond


Confused (未分類)

Characteristics:

  • Cannot determine which domain the problem belongs to.
  • Insufficient information to classify.

Action: Gather more information. Break the problem into smaller pieces that can be classified independently.


Framework Selection Matrix

Based on Cynefin classification, auto-select the framework combination:

Domain CHALLENGE Frameworks COMBINE Frameworks SHIFT Frameworks Intensity
Clear First Principles SCAMPER Reframing (E5) Light
Complicated Assumption Reversal, Devil's Advocate TRIZ, Cross-Domain Analogy Six Thinking Hats Medium
Complex Full Assumption Reversal (20+) Bisociation, TRIZ Reframing (Iceberg), Oblique Strategies, Multi-Agent Debate Heavy
Chaotic Quick Assumption List (5-10) Random Entry (Lateral) Oblique Strategies, PO Provocation Rapid
Confused First Principles (to decompose) — Reframing Matrix (4 perspectives) Diagnostic

Framework Intensity Guide

Intensity Assumptions Frameworks Combined Iterations Output Volume
Light 5-10 2-3 1 3 reframings
Medium 10-15 3-5 2 3-4 reframings
Heavy 15-20+ 5-7 2-3 4-5 reframings
Rapid 5-10 2-3 1 3 reframings (fast)
Diagnostic 10 1-2 1 Classification + next steps

Classification Procedure

Step 1: Gather Signals

Ask (or infer from context):

  • How well understood is the cause-effect relationship?
  • How many times has this type of problem been solved before?
  • How predictable are the outcomes of actions?
  • How many interacting systems/stakeholders are involved?
  • Is the situation stable or turbulent?

Step 2: Score

Criterion Clear (1) Complicated (2) Complex (3) Chaotic (4)
Cause-effect Obvious Discoverable Retrospective only None
Precedent Many times Some examples Few/none Unprecedented
Predictability High Medium Low None
Interactions Simple Moderate Many Overwhelming
Stability Stable Mostly stable Shifting Turbulent

Average score → domain classification.

Step 3: Validate

  • Does the classification feel right given the overall context?
  • Could the problem span multiple domains? (If so, decompose and classify each part.)
  • Is there a dominant domain with minor elements of another?

Step 4: Select Frameworks

Use the Framework Selection Matrix above. Adjust based on:

  • User's stated time constraints (→ reduce intensity).
  • User's expertise level (→ adjust explanation depth).
  • Specific user requests (→ include requested frameworks regardless of classification).

Edge Cases

Multi-Domain Problems

Some problems span domains. In this case:

  1. Decompose into sub-problems.
  2. Classify each independently.
  3. Apply appropriate frameworks to each.
  4. Synthesize at the CRYSTALLIZE phase.

Domain Transitions

Problems can shift domains over time:

  • Chaotic → Complex (after initial stabilization)
  • Complex → Complicated (as patterns emerge)
  • Complicated → Clear (as expertise develops)

If the user is describing a transition, apply frameworks for both domains.

User Override

If the user explicitly requests specific frameworks, honor the request regardless of Cynefin classification. Note the classification for context but follow user preference.

Source: SKILL.md on GitHub

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    The 'flux' skill is a problem-reframing and cognitive-bias auditing engine. It employs established intellectual frameworks such as Cynefin, TRIZ, and First Principles to transform user-provided problem statements into actionable reframes. The skill contains no malicious code, data exfiltration patterns, or unauthorized network operations, and its multi-engine execution relies on platform-standard CLI tools.

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