/ultra-think
Deep, multi-dimensional analysis and problem solving. Activates systematic reasoning across technical, business, user, and system perspectives. Generates multiple solutions with trade-offs, then synthesizes into a clear recommendation.
$ npx -y skills add coco-research/coco --skill ultra-think --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
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/ultra-think
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The summary Claude sees to decide when to auto-load this skill.
Deep, multi-dimensional analysis and problem solving. Activates systematic reasoning across technical, business, user, and system perspectives. Generates multiple solutions with trade-offs, then synthesizes into a clear recommendation.
SKILL.md
ultra-think.SKILL.mdname: ultra-think
description: "Deep, multi-dimensional analysis and problem solving. Activates systematic reasoning across technical, business, user, and system perspectives. Generates multiple solutions with trade-offs, then synthesizes into a clear recommendation."
domain: foundational
supports: [claude-code, cursor, codex, generic]
version: 0.1.0
Ultra Think — Deep Analysis Mode
Deep, multi-dimensional analysis and problem solving. Activates systematic reasoning across technical, business, user, and system perspectives. Generates multiple solutions with trade-offs, then synthesizes into a clear recommendation.
**Use when**: facing architectural decisions, complex trade-offs, strategic technology choices, system design problems, scaling challenges, migration decisions, or any question that deserves more than a quick answer. Attach this skill when you want rigorous, first-principles thinking.
---
When This Skill Is Activated
Do NOT jump to a solution. Follow every step below in order. Think deeply at each stage before moving on.
---
Step 1: Parse the Problem
Before analyzing, make sure you understand what's actually being asked.
- Extract the core challenge from the user's message
- Identify all stakeholders and constraints (stated and implied)
- Surface hidden complexities and implicit requirements
- Question assumptions — what is the user taking for granted?
- Name the unknowns explicitly
---
Step 2: Multi-Dimensional Analysis
Analyze the problem from four perspectives. Do not skip any.
Technical Perspective
- Feasibility and constraints
- Scalability, performance, maintainability
- Security implications
- Technical debt and future-proofing
- Integration complexity
Business Perspective
- Business value and ROI
- Time-to-market pressure
- Competitive advantage
- Risk vs. reward trade-offs
- Cost (development, operational, opportunity)
User Perspective
- User needs and pain points
- Usability and accessibility
- Edge cases and failure states from the user's point of view
- User journeys affected
System Perspective
- System-wide impacts and ripple effects
- Integration points and coupling
- Dependencies (upstream and downstream)
- Emergent behaviors and unintended interactions
---
Step 3: Generate Multiple Solutions
Brainstorm **at least 3 distinct approaches** — not variations of the same idea.
For each approach, evaluate:
- Pros and cons
- Implementation complexity (T-shirt size: S/M/L/XL)
- Resource requirements (people, time, money)
- Key risks
- Long-term implications (what does this look like in 2 years?)
Include at least one unconventional or creative solution. Consider hybrid approaches that combine strengths of different options.
---
Step 4: Deep Dive on Top Candidates
For the 1–2 most promising solutions:
- Sketch a detailed implementation plan (phases, milestones)
- Identify pitfalls and mitigation strategies
- Consider a phased approach or MVP path
- Analyze **second-order effects** — what changes because of this change?
- Think through failure modes — what happens when this breaks?
- Estimate reversibility — how hard is it to undo if wrong?
---
Step 5: Cross-Domain Thinking
Look beyond the immediate domain for insight:
- Are there parallels from other industries? (e.g., how did logistics solve this? Healthcare? Finance?)
- Do design patterns from other contexts apply? (e.g., circuit breakers from electrical engineering → software resilience)
- Are there natural system analogies? (e.g., biological redundancy, evolutionary pressure)
- Can existing solutions be combined in a novel way?
---
Step 6: Challenge and Stress-Test
Play devil's advocate against every solution, including the one you favor.
- What's the strongest argument against each option?
- What blind spots might you have?
- Run "what if" scenarios (what if traffic is 10x? what if the team halves? what if requirements change?)
- Stress-test assumptions — which ones, if wrong, would invalidate the whole approach?
- Look for unintended consequences
---
Step 7: Synthesize and Recommend
Combine all insights into a structured deliverable. Use this exact format:
## Problem Analysis
- **Core challenge**: [one sentence]
- **Key constraints**: [list]
- **Critical success factors**: [what must be true for any solution to work]
- **Assumptions**: [what we're taking as given]
## Solution Options
### Option 1: [Name]
- **Description**: [2-3 sentences]
- **Pros**: [list]
- **Cons**: [list]
- **Complexity**: [S/M/L/XL]
- **Risk level**: [Low/Medium/High]
- **Best when**: [conditions that make this the right choice]
### Option 2: [Name]
[Same structure]
### Option 3: [Name]
[Same structure]
## Recommendation
- **Recommended approach**: [which option and why]
- **Rationale**: [the decisive factors]
- **Implementation roadmap**: [phases with rough timelines]
- **Success metrics**: [how we'll know it's working]
- **Risk mitigation**: [top 3 risks and their mitigations]
- **Reversibility**: [how hard to undo if wrong]
## Contrarian View
- **The case against this recommendation**: [strongest counterargument]
- **What would change our mind**: [signals that we chose wrong]
- **Areas of uncertainty**: [what we don't know yet]
## Confidence Assessment
- **Overall confidence**: [High/Medium/Low] — [why]
- **What would increase confidence**: [additional research, prototyping, data needed]
---
Step 8: Meta-Reflection
End with a brief reflection:
- Where is the analysis weakest?
- What biases might be influencing the recommendation?
- What additional expertise or data would improve the analysis?
- What's the one thing most likely to be wrong?
---
Thinking Principles
Apply these mental models throughout the analysis:
| Principle | Application | |-----------|-------------| | **First Principles** | Break down to fundamental truths, don't reason by analogy alone | | **Systems Thinking** | Consider interconnections, feedback loops, eme
Read more
name: ultra-think description: "Deep, multi-dimensional analysis and problem solving. Activates systematic reasoning across technical, business, user, and system perspectives. Generates multiple solutions with trade-offs, then synthesizes into a clear recommendation." domain: foundational supports: [claude-code, cursor, codex, generic] version: 0.1.0
Ultra Think — Deep Analysis Mode
Deep, multi-dimensional analysis and problem solving. Activates systematic reasoning across technical, business, user, and system perspectives. Generates multiple solutions with trade-offs, then synthesizes into a clear recommendation.
**Use when**: facing architectural decisions, complex trade-offs, strategic technology choices, system design problems, scaling challenges, migration decisions, or any question that deserves more than a quick answer. Attach this skill when you want rigorous, first-principles thinking.
---
When This Skill Is Activated
Do NOT jump to a solution. Follow every step below in order. Think deeply at each stage before moving on.
---
Step 1: Parse the Problem
Before analyzing, make sure you understand what's actually being asked.
- Extract the core challenge from the user's message
- Identify all stakeholders and constraints (stated and implied)
- Surface hidden complexities and implicit requirements
- Question assumptions — what is the user taking for granted?
- Name the unknowns explicitly
---
Step 2: Multi-Dimensional Analysis
Analyze the problem from four perspectives. Do not skip any.
Technical Perspective
- Feasibility and constraints
- Scalability, performance, maintainability
- Security implications
- Technical debt and future-proofing
- Integration complexity
Business Perspective
- Business value and ROI
- Time-to-market pressure
- Competitive advantage
- Risk vs. reward trade-offs
- Cost (development, operational, opportunity)
User Perspective
- User needs and pain points
- Usability and accessibility
- Edge cases and failure states from the user's point of view
- User journeys affected
System Perspective
- System-wide impacts and ripple effects
- Integration points and coupling
- Dependencies (upstream and downstream)
- Emergent behaviors and unintended interactions
---
Step 3: Generate Multiple Solutions
Brainstorm **at least 3 distinct approaches** — not variations of the same idea.
For each approach, evaluate:
- Pros and cons
- Implementation complexity (T-shirt size: S/M/L/XL)
- Resource requirements (people, time, money)
- Key risks
- Long-term implications (what does this look like in 2 years?)
Include at least one unconventional or creative solution. Consider hybrid approaches that combine strengths of different options.
---
Step 4: Deep Dive on Top Candidates
For the 1–2 most promising solutions:
- Sketch a detailed implementation plan (phases, milestones)
- Identify pitfalls and mitigation strategies
- Consider a phased approach or MVP path
- Analyze **second-order effects** — what changes because of this change?
- Think through failure modes — what happens when this breaks?
- Estimate reversibility — how hard is it to undo if wrong?
---
Step 5: Cross-Domain Thinking
Look beyond the immediate domain for insight:
- Are there parallels from other industries? (e.g., how did logistics solve this? Healthcare? Finance?)
- Do design patterns from other contexts apply? (e.g., circuit breakers from electrical engineering → software resilience)
- Are there natural system analogies? (e.g., biological redundancy, evolutionary pressure)
- Can existing solutions be combined in a novel way?
---
Step 6: Challenge and Stress-Test
Play devil's advocate against every solution, including the one you favor.
- What's the strongest argument against each option?
- What blind spots might you have?
- Run "what if" scenarios (what if traffic is 10x? what if the team halves? what if requirements change?)
- Stress-test assumptions — which ones, if wrong, would invalidate the whole approach?
- Look for unintended consequences
---
Step 7: Synthesize and Recommend
Combine all insights into a structured deliverable. Use this exact format:
## Problem Analysis - **Core challenge**: [one sentence] - **Key constraints**: [list] - **Critical success factors**: [what must be true for any solution to work] - **Assumptions**: [what we're taking as given] ## Solution Options ### Option 1: [Name] - **Description**: [2-3 sentences] - **Pros**: [list] - **Cons**: [list] - **Complexity**: [S/M/L/XL] - **Risk level**: [Low/Medium/High] - **Best when**: [conditions that make this the right choice] ### Option 2: [Name] [Same structure] ### Option 3: [Name] [Same structure] ## Recommendation - **Recommended approach**: [which option and why] - **Rationale**: [the decisive factors] - **Implementation roadmap**: [phases with rough timelines] - **Success metrics**: [how we'll know it's working] - **Risk mitigation**: [top 3 risks and their mitigations] - **Reversibility**: [how hard to undo if wrong] ## Contrarian View - **The case against this recommendation**: [strongest counterargument] - **What would change our mind**: [signals that we chose wrong] - **Areas of uncertainty**: [what we don't know yet] ## Confidence Assessment - **Overall confidence**: [High/Medium/Low] — [why] - **What would increase confidence**: [additional research, prototyping, data needed]
---
Step 8: Meta-Reflection
End with a brief reflection:
- Where is the analysis weakest?
- What biases might be influencing the recommendation?
- What additional expertise or data would improve the analysis?
- What's the one thing most likely to be wrong?
---
Thinking Principles
Apply these mental models throughout the analysis:
| Principle | Application | |-----------|-------------| | **First Principles** | Break down to fundamental truths, don't reason by analogy alone | | **Systems Thinking** | Consider interconnections, feedback loops, eme
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