prometheus-sequential-thinking

MANDATORY USAGE (CRITICAL RULE)

This skill is MANDATORY for all agents in the ULTRABRAIN category.

When ULTRABRAIN is used:

• Deep logical reasoning tasks
• Complex architecture decisions requiring extensive analysis
• System design (monolith vs microservices, database choices)
• Technology selection (frameworks, libraries, patterns)
• Long-term architectural planning (scalability, maintainability)
• Security and compliance design
• High-risk refactoring
• Migrating monoliths to microservices
• Changing core data structures or APIs
• Performance optimizations affecting multiple modules
• Uncertain requirements (vague requests, investigation needed)

ALL ULTRABRAIN agents MUST use the sequantial-thinking-mcp_sequentialthinking tool before making any decisions, recommendations, or plans.

Agents that MUST use this skill:

• Atlas (when delegating to ultrabrain category)
• Sisyphus (when working on ultrabrain tasks)
• Prometheus (when planning architecture/complex decisions)
• Sisyphus-Juneor-ultrabrain (ALL instances)
• Any agent receiving category="ultrabrain" delegation

What I do

This skill guides agents on when and how to use the server-sequential-thinking MCP tool to improve the quality of their reasoning, planning, and decision-making processes.

The sequential-thinking tool enables:

• Step-by-step analysis with hypothesis formation and verification
• Branching thoughts to explore alternative approaches
• Revision of previous thoughts to reconsider decisions
• Extension of analysis even after reaching initial conclusions
• Expressing uncertainty when information is insufficient

When to use me

Use sequential-thinking when working on tasks that benefit from deep, structured analysis:

Trigger Categories

Specific Scenarios

Use for ARCHITECTURE tasks:

• System design decisions (monolith vs microservices, database choices)
• Technology selection (frameworks, libraries, patterns)
• Long-term architectural planning (scalability, maintainability)
• Security and compliance design

Use for HIGH-COMPLEXITY refactoring:

• Migrating monoliths to microservices
• Changing core data structures or APIs
• Removing technical debt with wide impact
• Performance optimizations affecting multiple modules

Use for UNCERTAIN requirements:

• User provides vague requests ("optimize data", "improve UX")
• Need to investigate before planning
• Multiple possible interpretations of requirements
• Research-heavy tasks with open-ended goals

When NOT to use me

Skip sequential-thinking for:

• Yes/no questions with clear answers
• Syntax lookup or documentation queries
• Single-line typo fixes
• Adding obvious features with clear scope
• Simple configuration changes
• Formatting or style-only tasks

How to use me

Tool Invocation

The tool is named sequantial-thinking-mcp_sequentialthinking (note: "sequantial" is intentional, not a typo).

Parameters

Usage Pattern

1. Start with estimate: Set thoughtNumber: 1, totalThoughts: N (your initial guess)
2. Build incrementally: Each thought builds on previous analysis
3. Adjust as needed: Can increase totalThoughts if discovering more complexity
4. Reconsider when uncertain: Use isRevision: true to question previous conclusions
5. Branch for alternatives: Use branchFromThought to explore different approaches
6. Signal completion: Set nextThoughtNeeded: false when satisfied with analysis
7. Can extend after "end": Use needsMoreThoughts: true if realizing more analysis needed

Recommended Limits

• 5-7 thoughts for typical analysis
• Avoid overthinking (10+ thoughts) unless task is exceptionally complex
• Use branching instead of single long thought chain for multiple alternatives

Advanced Features

Branching:

Thought 1: Analyze problem
Thought 2: Consider approach A
Thought 3: Branch to approach B (branchFromThought=2, branchId="alt-b")
  → Explore alternative without losing approach A context

Revision:

Thought 3: Decision: Use X
Thought 4: Realize X has problem Y
Thought 5: isRevision=true, revisesThought=3, "Reconsider: X may not work because Y"

Extension:

Thought 5: Conclusion: Use approach A
Thought 6: needsMoreThoughts=true, "Wait, just realized constraint Z breaks A"

Example Scenarios

Example 1: Architecture Decision

Task: "Design authentication system for our app"

Sequential-Thinking Session:

Thought 1: Analyze requirements - what auth providers needed? (OAuth, JWT, session?)
  Consider: User base, security needs, existing infrastructure
  nextThoughtNeeded: true

Thought 2: Evaluate options
  - NextAuth.js: Fast setup, integrates well with our stack
  - Custom JWT: More control, more work
  - Session-based: Simpler, less scalable
  Trade-offs: Setup time vs flexibility vs performance
  nextThoughtNeeded: true

Thought 3: Predict long-term consequences
  NextAuth: Easy now, but provider updates could break things
  Custom JWT: More work now, but full control over upgrades
  Session: Scaling issues if user count grows significantly
  nextThoughtNeeded: true

Thought 4: Formulate hypothesis
  Recommendation: NextAuth.js for rapid development
  Rationale: Our timeline is tight, NextAuth covers most providers
  Risk: Future provider updates require testing
  nextThoughtNeeded: true

Thought 5: Verify hypothesis
  Does NextAuth align with requirements?
  - Provider support: Yes (Google, GitHub, email)
  - Security: Good, battle-tested
  - Timeline: Fits constraints
  Conclusion: Hypothesis validated
  nextThoughtNeeded: false

Result: Well-reasoned architecture recommendation with documented trade-offs and risks.

Example 2: Complex Refactoring

Task: "Migrate monolithic auth service to microservices"

Sequential-Thinking Session:

Thought 1: Map current dependencies
  Which modules depend on auth service?
  - User profile module (heavy coupling)
  - Payment gateway (needs user verification)
  - Analytics (tracks auth events)
  Risk: Breaking changes could cascade across system
  nextThoughtNeeded: true

Thought 2: Identify failure points
  - Direct database access from multiple services
  - Shared auth token generation logic
  - Synchronous auth checks (latency bottlenecks)
  nextThoughtNeeded: true

Thought 3: Design migration strategy
  Option A: Big bang - all at once
  Option B: Incremental - feature by feature
  Risk analysis:
  - A: High risk, no rollback path
  - B: Lower risk, but longer timeline with dual maintenance
  nextThoughtNeeded: true

Thought 4: Plan rollback strategy
  If Option B fails:
  - Keep old service running as fallback
  - Feature flags to switch back
  - Data sync to prevent inconsistency
  nextThoughtNeeded: true

Thought 5: Define test verification
  - Load test before migration
  - Integration tests for cross-service communication
  - Monitor auth latency during rollout
  nextThoughtNeeded: true

Thought 6: Final plan
  Strategy: Incremental migration (Option B)
  Timeline: 4 phases, 2 weeks each
  Rollback: Feature flags, old service on standby
  Testing: Load test + integration tests + monitoring
  nextThoughtNeeded: false

Result: Safe migration plan with clear phases, rollback options, and verification steps.

Example 3: Uncertain Requirements

Task: User says "We need to optimize data performance"

Sequential-Thinking Session:

Thought 1: What does "data" mean?
  Possibilities:
  - Database query performance
  - API response times
  - Data processing pipelines
  - Analytics/aggregation speed
  Uncertainty: Cannot plan without clarifying scope
  nextThoughtNeeded: true

Thought 2: Hypothesize use cases
  Branch A: User-facing performance (UI loading, API calls)
  Branch B: Internal performance (batch jobs, analytics)
  Branch C: Storage/cost optimization (database sizing, caching)
  Each branch has very different solutions
  nextThoughtNeeded: true

Thought 3: Branch A exploration (UI/API)
  If this is the issue:
  - Caching strategy (Redis, CDN)
  - Database indexing
  - API response pagination
  nextThoughtNeeded: true

Thought 4: Branch B exploration (internal)
  If this is the issue:
  - Batch job parallelization
  - ETL pipeline optimization
  - Message queuing (Kafka, RabbitMQ)
  nextThoughtNeeded: true

Thought 5: Branch C exploration (storage)
  If this is the issue:
  - Database sharding
  - Data compression
  - Archive old data
  nextThoughtNeeded: true

Thought 6: Formulate questions for user
  Before planning, ask:
  1. Is this about user-facing performance (API/UI) or internal jobs?
  2. What are the current pain points? (slow loading, timeouts, high costs?)
  3. Any specific metrics? (response time > 2s, CPU > 80%, storage > 10TB?)
  4. Any constraints? (budget, timeline, tech stack limits?)
  Rationale: Answers will narrow down to one branch
  nextThoughtNeeded: false

Result: Targeted, context-aware questions that quickly identify actual requirements.

Integration Points

Before Interview Questions

Use sequential-thinking when requirements are unclear to frame better questions:

Example: Before asking "What do you want?", first analyze:

• What information is missing?
• What assumptions can I make?
• What clarifying questions will be most valuable?

Benefit: More focused, productive interview sessions.

After Explore/Librarian Research

Use sequential-thinking to synthesize multiple sources of information:

Example: After gathering context from codebase and docs, use to:

• Identify patterns and contradictions
• Form a coherent understanding
• Generate informed questions or recommendations

Benefit: Deeper insights than surface-level synthesis.

Before Plan Generation

Use sequential-thinking to verify logical consistency of planned approach:

Example: Before generating tasks, analyze:

• Does the approach address all requirements?
• Are there logical gaps or contradictions?
• Are dependencies correctly ordered?
• Are acceptance criteria realistic?

Benefit: Higher-quality plans with fewer revisions.

During Complex Decisions

Use sequential-thinking when weighing alternatives:

Example: When choosing between multiple technical options:

• Evaluate trade-offs (performance, maintainability, complexity)
• Predict long-term consequences
• Identify risk factors
• Formulate justified recommendation

Benefit: Well-reasoned decisions with documented rationale.

Anti-Patterns (Don't do this)

Don't use sequential-thinking for:

• Syntax queries ("How do I write a for loop in Python?") → Use documentation or librarian
• Yes/no questions with clear answers → Direct answer is faster
• Simple code changes with clear scope → Overhead not justified
• Trivial bug fixes → Just fix it
• Formatting/style-only tasks → Use linter or formatter

Fallback Guidance

If sequential-thinking MCP is unavailable or errors occur:

1. Continue with standard workflow - The tool enhances but is not required
2. Document uncertainty - If stuck, note what information is missing
3. Ask clarifying questions - Engage user when requirements are unclear
4. Use other agents - Oracle for architecture, Librarian for research

The skill is designed to enhance planning, not block it.

Summary

Use this skill to:

• Make better decisions for complex, high-stakes tasks
• Avoid overlooking important considerations
• Provide well-reasoned recommendations with clear rationale
• Structure your thinking when problems are ambiguous

Key principle: Sequential-thinking is a tool, not a mandate. Use it when it adds value, skip it when it doesn't.