Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
version
1.1.0
model
sonnet
invoked_by
both
user_invocable
true
tools
["Read","Write"]
feature_flag
ELICITATION_ENABLED
best_practices
["Use for important decisions, complex problems, or critical outputs","Not for simple queries or routine tasks","Budget 2x LLM cost vs regular responses"]
error_handling
graceful
streaming
supported
verified
true
lastVerifiedAt
"2026-02-22T00:00:00.000Z"
source
builtin
trust_score
100
provenance_sha
a83edf6c6c4e74e0
Advanced Elicitation
Overview
Meta-cognitive reasoning applied to AI outputs. Makes AI reconsider its own work through 15+ systematic methods.
Core Principle: First-pass responses are often good but not great. Elicitation forces deeper thinking.
When to Use
Use when:
Making important decisions (architecture, security, major features)
Apply Elicitation Method: Pick 1-3 methods based on context
Reconsider: Agent re-evaluates using method
Synthesize: Combine insights, produce improved output
Elicitation Methods
1. First Principles Thinking
Description: Break down to fundamental truths, rebuild reasoning from ground up
When to Use:
Complex system design
Architecture decisions
Innovation challenges
Prompt Template:
You are applying First Principles Thinking to:
---
{content}
---
Steps:
1. List all underlying assumptions
2. Question each assumption: "Is this fundamentally true?"
3. Identify fundamental truths (cannot be broken down further)
4. Rebuild solution from fundamentals only
5. Compare rebuilt solution to original - what changed?
Output:
### First Principles Analysis
**Fundamental Truths:**
- [Truth 1]
- [Truth 2]
**Assumptions Challenged:**
1. [Assumption] - [Why it might be wrong]
**Improvements:**
- [Improvement based on fundamentals]
**Confidence Level:** [HIGH/MEDIUM/LOW]
2. Pre-Mortem Analysis
Description: Imagine the solution failed. Work backward to identify causes.
When to Use:
Planning major changes
Risk mitigation
Launch preparations
Prompt Template:
You are applying Pre-Mortem Analysis to:
---
{content}
---
Steps:
1. Fast-forward 6 months: the solution has failed spectacularly
2. List 5 reasons why it failed
3. For each reason, assess likelihood (Low/Medium/High)
4. For each high-likelihood failure, propose mitigation
5. Revise original solution with mitigations
Output:
### Pre-Mortem Analysis
**Failure Scenarios:**
1. [Scenario] - Likelihood: [L/M/H]
2. [Scenario] - Likelihood: [L/M/H]
**Mitigations:**
- [Mitigation for high-likelihood failures]
**Revised Solution:**
- [Changes to prevent failures]
**Confidence Level:** [HIGH/MEDIUM/LOW]
3. Socratic Questioning
Description: Challenge every assumption with "why?" until reaching bedrock.
When to Use:
Requirements analysis
Specification review
Clarifying ambiguity
Prompt Template:
You are applying Socratic Questioning to:
---
{content}
---
Steps:
1. Identify 5 key claims in the content
2. For each claim, ask "Why is this true?"
3. For the answer, ask "Why?" again
4. Repeat until you hit a contradiction or fundamental truth
5. Revise claims that don't survive questioning
Output:
### Socratic Analysis
**Claim 1:** [Claim]
- Why? [Answer]
- Why? [Answer]
- Why? [Answer]
- **Verdict:** [Survives/Needs revision]
**Improvements:**
- [Changes after questioning]
**Confidence Level:** [HIGH/MEDIUM/LOW]
4. Red Team vs Blue Team
Description: Attack the solution (Red Team), defend it (Blue Team), synthesize improvements.
When to Use:
Security reviews
Risk assessment
Adversarial testing
Prompt Template:
You are applying Red Team vs Blue Team to:
---
{content}
---
Steps:
1. **Red Team**: List 5 ways to attack/break this solution
2. **Blue Team**: For each attack, propose a defense
3. **Red Team**: For each defense, find the weakness
4. **Blue Team**: Strengthen defenses
5. Synthesize: What changes make the solution more robust?
Output:
### Red Team vs Blue Team
**Attack 1:** [How to break it]
- Defense: [Blue team response]
- Counter-attack: [Red team finds weakness]
- Final defense: [Blue team strengthens]
**Improvements:**
- [Robust changes from adversarial testing]
**Confidence Level:** [HIGH/MEDIUM/LOW]
5. Inversion
Description: Instead of "How to succeed?", ask "How to fail?" and avoid those.
When to Use:
Risk identification
Avoiding common pitfalls
Negative space analysis
Prompt Template:
You are applying Inversion to:
---
{content}
---
Steps:
1. Invert the goal: "How could we make this FAIL?"
2. List 5 ways to guarantee failure
3. For each failure mode, identify the opposite (success mode)
4. Check if original solution addresses success modes
5. Revise to explicitly avoid failure modes
Output:
### Inversion Analysis
**How to Fail:**
1. [Failure mode]
2. [Failure mode]
**How to Succeed (inverses):**
1. [Success mode]
**Improvements:**
- [Changes to avoid failures]
**Confidence Level:** [HIGH/MEDIUM/LOW]
6. Second-Order Thinking
Description: Consider consequences of consequences. Long-term effects.
When to Use:
Strategic decisions
Long-term planning
Trade-off analysis
Prompt Template:
You are applying Second-Order Thinking to:
---
{content}
---
Steps:
1. Identify immediate consequences (1st order)
2. For each consequence, identify follow-on effects (2nd order)
3. For each 2nd order effect, identify further effects (3rd order)
4. Assess whether long-term effects align with goals
5. Revise solution to optimize for 2nd/3rd order effects
Output:
### Second-Order Analysis
**1st Order:** [Immediate effect]
- **2nd Order:** [Consequence of consequence]
- **3rd Order:** [Further consequence]
**Long-Term Implications:**
- [Good/Bad long-term effects]
**Improvements:**
- [Changes optimizing for long-term]
**Confidence Level:** [HIGH/MEDIUM/LOW]
You are applying SWOT Analysis to:
---
{content}
---
Steps:
1. **Strengths**: What are the advantages?
2. **Weaknesses**: What are the disadvantages?
3. **Opportunities**: What external factors could help?
4. **Threats**: What external factors could harm?
5. Synthesize: How to leverage S+O, mitigate W+T?
Output:
### SWOT Analysis
**Strengths:**
- [Internal advantage]
**Weaknesses:**
- [Internal disadvantage]
**Opportunities:**
- [External positive factor]
**Threats:**
- [External negative factor]
**Strategy:**
- [Leverage strengths/opportunities, mitigate weaknesses/threats]
**Confidence Level:** [HIGH/MEDIUM/LOW]
8. Opportunity Cost Analysis
Description: What are we NOT doing? What are we giving up?
When to Use:
Prioritization
Resource allocation
Trade-off decisions
Prompt Template:
You are applying Opportunity Cost to:
---
{content}
---
Steps:
1. List what this solution requires (time, money, people)
2. List 3 alternative uses for those resources
3. For each alternative, estimate value
4. Compare: Is this solution the highest-value use?
5. If not, propose reallocation
Output:
### Opportunity Cost Analysis
**Resources Required:**
- [Time/Money/People]
**Alternatives:**
1. [Alternative use] - Estimated value: [X]
2. [Alternative use] - Estimated value: [Y]
**Verdict:**
- [Is this the best use? Why/why not?]
**Improvements:**
- [Reallocations or justifications]
**Confidence Level:** [HIGH/MEDIUM/LOW]
9. Analogical Reasoning
Description: How have others solved similar problems? Learn from analogies.
When to Use:
Innovation
Learning from history
Cross-domain insights
Prompt Template:
You are applying Analogical Reasoning to:
---
{content}
---
Steps:
1. Identify the core problem (abstract it)
2. Find 3 analogous situations (other domains/times)
3. How was the analogous problem solved?
4. What lessons transfer to this situation?
5. Adapt the solution based on analogies
Output:
### Analogical Analysis
**Core Problem:** [Abstract problem statement]
**Analogy 1:** [Domain/situation]
- How they solved it: [Solution]
- Lesson: [What transfers]
**Improvements:**
- [Adapted solution from analogies]
**Confidence Level:** [HIGH/MEDIUM/LOW]
10. Constraint Relaxation
Description: What if constraint X didn't exist? How would that change the solution?
When to Use:
Innovation
Breaking assumptions
Finding creative solutions
Prompt Template:
You are applying Constraint Relaxation to:
---
{content}
---
Steps:
1. List all constraints (explicit and implicit)
2. For each constraint, ask: "What if this wasn't true?"
3. Design solution without that constraint
4. Assess: Can we actually relax this constraint?
5. If yes, propose new solution. If no, learn from the thought experiment.
Output:
### Constraint Relaxation
**Constraint:** [Constraint]
- **If removed:** [Solution without constraint]
- **Can we actually relax it?** [Yes/No + reasoning]
**Improvements:**
- [Creative solutions from relaxation]
**Confidence Level:** [HIGH/MEDIUM/LOW]
11. Failure Modes and Effects Analysis (FMEA)
Description: What could go wrong? How likely? How bad? Prioritize fixes.
When to Use:
Engineering design
Risk assessment
Safety-critical systems
Prompt Template:
You are applying FMEA to:
---
{content}
---
Steps:
1. List all components/steps in the solution
2. For each, identify potential failure modes
3. Rate each: Severity (1-10), Likelihood (1-10)
4. Calculate Risk Priority Number (RPN = Severity × Likelihood)
5. Address high-RPN failures first
Output:
### FMEA
**Failure Mode 1:** [What fails]
- Severity: [1-10]
- Likelihood: [1-10]
- RPN: [Product]
- Mitigation: [How to prevent/detect/recover]
**Improvements:**
- [Prioritized mitigations for high-RPN failures]
**Confidence Level:** [HIGH/MEDIUM/LOW]
12. Bias Check
Description: What cognitive biases might affect this? Correct for them.
When to Use:
Decision-making
Review processes
Self-critique
Prompt Template:
You are applying Bias Check to:
---
{content}
---
Steps:
1. Review common cognitive biases (confirmation, anchoring, sunk cost, availability, etc.)
2. For each bias, ask: "Is this affecting my reasoning?"
3. Find evidence of bias in the original content
4. Correct for identified biases
5. Re-evaluate the solution bias-free
Output:
### Bias Check
**Bias Detected:** [Bias name]
- **Evidence:** [Where it appears]
- **Correction:** [Adjusted reasoning]
**Improvements:**
- [Bias-free solution]
**Confidence Level:** [HIGH/MEDIUM/LOW]
13. Base Rate Thinking
Description: What usually happens in similar situations? Are we being overconfident?
When to Use:
Estimation
Risk assessment
Reality-checking optimism
Prompt Template:
You are applying Base Rate Thinking to:
---
{content}
---
Steps:
1. Identify the reference class (similar past situations)
2. What's the base rate (average outcome for reference class)?
3. Why might this case be different?
4. Adjust estimates toward base rate (Bayesian update)
5. Revise solution with realistic expectations
Output:
### Base Rate Analysis
**Reference Class:** [Similar situations]
- **Base Rate:** [Typical outcome]
- **Our Estimate:** [Original estimate]
- **Adjusted Estimate:** [Reality-checked estimate]
**Improvements:**
- [More realistic solution]
**Confidence Level:** [HIGH/MEDIUM/LOW]
14. Steelmanning
Description: What's the strongest version of an opposing view? Address that, not a strawman.
When to Use:
Proposal review
Debate preparation
Intellectual honesty
Prompt Template:
You are applying Steelmanning to:
---
{content}
---
Steps:
1. Identify the opposing view (or alternative approach)
2. Strengthen it: What's the BEST argument against your solution?
3. Address the strong version (not a weak strawman)
4. If the steelman wins, adopt that approach
5. If your solution survives, it's stronger
Output:
### Steelman Analysis
**Opposing View:** [Alternative]
- **Strongest Argument:** [Best case for alternative]
- **Response:** [Addressing the strong version]
- **Verdict:** [Which approach is better?]
**Improvements:**
- [Refined solution after facing steelman]
**Confidence Level:** [HIGH/MEDIUM/LOW]
15. Time Horizon Shift
Description: How does this look in 1 hour? 1 day? 1 month? 1 year? 5 years?
When to Use:
Long-term planning
Trade-off analysis
Strategy evaluation
Prompt Template:
You are applying Time Horizon Shift to:
---
{content}
---
Steps:
1. Evaluate solution at 1 hour: [Impact]
2. Evaluate at 1 day: [Impact]
3. Evaluate at 1 month: [Impact]
4. Evaluate at 1 year: [Impact]
5. Evaluate at 5 years: [Impact]
6. Identify time-horizon-dependent trade-offs
7. Optimize for the right time horizon
Output:
### Time Horizon Analysis
**1 Hour:** [Short-term effect]
**1 Day:** [Effect]
**1 Month:** [Effect]
**1 Year:** [Effect]
**5 Years:** [Long-term effect]
**Trade-Offs:**
- [Short vs long-term conflicts]
**Improvements:**
- [Optimized for appropriate horizon]
**Confidence Level:** [HIGH/MEDIUM/LOW]
Skill({ skill: 'advanced-elicitation', args: 'auto' });
// Automatically picks 2-3 methods based on content analysis
Integration with spec-critique
Advanced Elicitation can enhance spec-critique:
// After generating specSkill({ skill: 'spec-critique', args: 'with-elicitation' });
// Applies elicitation to critique process
Cost Control (per ADR-053)
Opt-in only: Never applied automatically
Budget limit: Configurable via ELICITATION_BUDGET_LIMIT
Cost tracking: Integrates with cost-tracking hook
Config:
features:advancedElicitation:enabled:truecostBudget:10.0# USD per sessionminConfidence:0.7# Skip if confidence highmaxMethodsPerInvocation:5# SEC-AE-001maxInvocationsPerSession:10# SEC-AE-003
Security Controls
SEC-AE-001: Input Validation
Method names must match /^[a-z][a-z0-9-]*$/
Max 5 methods per invocation
Invalid methods rejected with error
SEC-AE-002: Cost Budget Enforcement
Check session budget before elicitation
Track cumulative cost
Fail gracefully if budget exceeded
SEC-AE-003: Rate Limiting
Max 10 elicitations per session
Prevent runaway elicitation loops
Clear error message on limit
Examples
Example 1: Architecture Decision
Before Elicitation:
We should use microservices with 12 services communicating via REST.
After First Principles:
Fundamental truths: Services must communicate, data must be consistent.
Challenged assumption: "12 services" - is this the right granularity?
Could 6 bounded contexts suffice?
Improvement: Consolidate to 6-8 services by bounded context.
Use gRPC internally (40% latency reduction vs REST).
Example 2: Security Review
Before Elicitation:
JWT tokens for authentication across services.
After Red Team/Blue Team:
Red Team Attack: Token theft via XSS, JWT validation on every call (latency).
Blue Team Defense: HttpOnly cookies, service mesh mTLS instead of JWT propagation.
Improvement: Use service mesh (Istio) for security instead of JWT propagation.
Example 3: Spec Validation
Before Elicitation:
Feature: User can delete their account.
After Pre-Mortem:
Failure Scenario: 6 months later, GDPR compliance audit fails.
Cause: Deletion didn't cascade to all systems (analytics, backups).
Improvement: Add "Data Retention Audit" requirement.
Specify cascade delete to all systems within 30 days.
Performance
Quality Improvement: +30% (measured on critical decisions)
Cost: 2x LLM usage
Time: +50% (worth it for important work)
Memory Protocol (MANDATORY)
Before starting:
cat .claude/context/memory/learnings.md
After completing:
New pattern → .claude/context/memory/learnings.md
Issue found → .claude/context/memory/issues.md
Decision made → .claude/context/memory/decisions.md
ASSUME INTERRUPTION: If it's not in memory, it didn't happen.
Iron Laws
NEVER apply elicitation automatically — it is always opt-in. Never invoke without explicit user request or clear agent intent signal.
ALWAYS emit a confidence level for every method output — HIGH / MEDIUM / LOW is mandatory. Outputs without calibration are not actionable.
NEVER exceed 5 methods per invocation (SEC-AE-001) — over-elicitation produces noise, not signal. Select 1-3 most relevant methods.
ALWAYS check session budget before invoking — fail gracefully with a clear message when ELICITATION_BUDGET_LIMIT is exceeded (SEC-AE-002).
NEVER treat elicitation as a substitute for evidence — it refines reasoning; it does not produce facts. Always ground conclusions in codebase evidence.
Anti-Patterns
Anti-Pattern
Why It Fails
Correct Approach
Auto-applying to every response
2× cost with no benefit for simple tasks
Opt-in only for important/complex decisions
Running all 15 methods at once
Diminishing returns, token explosion
Select 1–3 most relevant methods
Skipping confidence rating
Evaluation without calibration is useless
Always emit **Confidence Level:** HIGH/MEDIUM/LOW
Elicitation replaces evidence
Reasoning without facts is speculation
Pair with grounded codebase evidence before eliciting
No budget check
Session cost spirals undetected
Always verify ELICITATION_BUDGET_LIMIT before invoking
Running after deadline/emergency
High cost with no time to act on improvements
Skip for time-critical fixes; use for strategic work
