Second Opinion Skill
Proactively suggest getting another LLM's perspective when the situation warrants it.
Trigger Conditions
Suggest a second opinion when you detect:
- Architectural Decisions
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Choosing between design patterns (e.g., repository vs service layer)
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Database schema design decisions
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API design choices (REST vs GraphQL, versioning strategy)
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Service decomposition (monolith vs microservices)
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State management approaches
- Complex Trade-offs
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Performance vs. readability
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Flexibility vs. simplicity
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DRY vs. explicit code
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Build vs. buy decisions
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Consistency vs. availability trade-offs
- Critical Code Reviews
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Security-sensitive code (authentication, authorization, crypto)
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Performance-critical paths
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Complex algorithms or data structures
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Code handling financial transactions or PII
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Concurrency and threading logic
- Explicit Requests (trigger words)
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"another perspective"
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"second opinion"
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"sanity check"
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"what do you think"
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"am I on the right track"
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"does this make sense"
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"is this a good approach"
How to Suggest
When conditions are met, offer specific options:
This involves [type of decision]. Would you like a second opinion from another LLM?
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/codex review
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Get OpenAI's analysis
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/gemini <specific question>
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Ask Google Gemini
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/ollama <question>
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Use a local model (keeps data private)
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/llm-compare <question>
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Compare multiple models
Tailor the suggestion to the context:
For security-sensitive code:
Since this involves authentication logic, you might want a second security review. Try /codex review or /ollama (keeps code local) for another perspective.
For architectural decisions:
This is a significant architectural choice. Different models sometimes weigh trade-offs differently. Want to try /llm-compare "should I use X or Y for this use case" to see multiple perspectives?
For complex algorithms:
This algorithm has some complexity. A second set of eyes might catch edge cases. Try /codex explain the edge cases in this algorithm .
When NOT to Suggest
Do not suggest second opinions when:
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User is actively implementing (don't interrupt flow)
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Task is simple/straightforward (typos, formatting, simple fixes)
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User has already made a firm decision
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User said "just do it" or similar
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It's routine code changes with clear requirements
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User previously declined suggestions in this session
Privacy Consideration
Always mention /ollama as an option when the code might be sensitive:
For proprietary code, /ollama keeps everything local - your code never leaves your machine.
Example Interactions
Example 1: Architectural Decision
User: "Should I use a monorepo or multi-repo for these microservices?"
Suggest:
Both approaches have valid trade-offs that depend on your team size and deployment needs. For a decision this impactful, would you like another perspective?
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/codex explain trade-offs between monorepo and multi-repo
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/llm-compare to see how different models weigh the factors
Example 2: Security Code Review
User: "Can you review this JWT validation code?"
After providing your review, suggest:
Since this is security-critical authentication code, you might want a second review:
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/codex review for OpenAI's security analysis
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/ollama review this JWT implementation (keeps code private)
Example 3: Complex Algorithm
User: "Does this concurrent queue implementation look correct?"
After analysis, suggest:
Concurrent code can have subtle race conditions. Want a second opinion?
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/codex analyze race conditions in this code
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/gemini explain potential deadlocks here
Example 4: Design Pattern Choice
User: "Should I use the factory pattern or builder pattern here?"
Suggest:
Both patterns could work here with different trade-offs. Want to see how other models approach this?
- /llm-compare "factory vs builder pattern for <context>" for multiple perspectives
Integration with Other Commands
When suggesting, be specific about which command fits best:
Situation Best Command
Code review /codex review
Quick question /gemini <question>
Sensitive/private code /ollama <question>
Want multiple views /llm-compare <question>
Complex reasoning task /codex or /ollama with larger models