think-twice

Think Twice

Wrong skill? Research a topic → perplexity-research. Brainstorm solutions → brainstorming. Debug a specific error → systematic-debugging.

Break through blockers by consulting a fresh perspective.

When to Use

• You've tried the same approach 3+ times without progress
• You notice yourself using hedging language ("I'm not sure why")
• The same error keeps recurring after attempted fixes
• You catch yourself referencing your own failed output as evidence

Process

1. Generate consultation prompt (see references/consultation-prompt-template.md): Problem statement, technical context, what was tried + outcomes, exact error messages, minimal code snippet, constraints, specific ask. Must be self-contained, <2000 tokens.

2. Ask user: "Want to review the prompt before I dispatch, or send now?"

3. Dispatch (in priority order):

   • Sub-agent (sub-agent-explore) — free, instant
   • Perplexity reason — only if THINK_TWICE_USE_PERPLEXITY=true in .env (~$0.01/query)
   • Manual fallback — save prompt to file, user pastes into another LLM

4. Score response: Relevance (30%) + Novelty (25%) + Specificity (25%) + Feasibility (20%). Report score, key recommendations, suggested next step.

5. If score <50: Offer retry with refined prompt (max 1 retry) or proceed with best suggestion.

Stuck-Signal Auto-Detection

Continuously monitor for these signals. When cumulative score ≥ 7, invoke think-twice automatically:

Signal	Weight
Same fix tried 3+ times	3
Circular reasoning (referencing own failed output)	3
Same error 3+ times after fixes	3
Exhaustion language ("I've tried everything")	3
Uncertainty hedging ("I'm not sure why")	2
Approach change without rationale	2

Escalation Path

Problem Type	First	Escalate To
Reasoning (logic, approach, design)	think-twice	perplexity-research
Knowledge (API docs, error codes, facts)	perplexity-research	think-twice for fresh reasoning
Both (stuck + need facts)	think-twice	perplexity-research with refined query

⚠️ Cost gate: perplexity-research calls a paid API. Before escalating, confirm the knowledge gap cannot be resolved with a web search or by re-reading existing context. If escalating: inform the user a paid API call is being made.

Consultation Prompt Quality

The prompt sent to the sub-agent determines outcome quality. MUST include:

Element	Required?	Why
Problem statement	✅	What's broken or stuck
Technical context	✅	Stack, versions, constraints
What was tried + outcomes	✅	Prevents re-trying failed approaches
Exact error messages	✅	Enables pattern matching
Minimal code snippet	✅	Concrete not abstract
Constraints	✅	What CAN'T change
Specific ask	✅	"What else could cause X?" not "help"

Total: <2000 tokens. Self-contained. No references to "above" or "earlier."

References

• references/consultation-prompt-template.md — Prompt template
• references/scoring-rubric.md — Scoring dimensions
• prompts/consultant-persona.md — Sub-agent persona

Failure Modes

Failure	Fix
Sub-agent inherits same flawed assumptions	Provide raw symptoms only, not prior conclusions
Agent ignores stuck signals and keeps looping	Enforce cumulative score threshold — 7+ is mandatory
Fresh perspective is too shallow	Sub-agent must produce root-cause hypothesis, not just "try X"

# Example: invoke think-twice when stuck
node ~/.codex/superpowers-augment/superpowers-augment.js use-skill think-twice

Companion Skills

• perplexity-research: Escalation target for knowledge problems
• systematic-debugging: For specific error debugging
• brainstorming: For generating alternative approaches
• adversarial-search: Confirmation bias prevention
• investigation-state: When investigation hits a wall
• issue-comment-debunker: Debunking suspicious issue claims
• experimental-self-prompting: Self-directed exploration
• quantitative-decision-gate: Quantitative decision-making
• failure-autopsy: Post-mortem analysis
• micro-harsh-review: Per-batch code review