| name | gg - Guess Generation (Exhaustive Search with Coverage Tracking) |
| description | Generate exhaustive guesses about user input using ALL search methods with coverage tracking. Guessing is SEARCH through possibility space. Tracks space created vs space covered to ensure comprehensive exploration. |
| output | {"format":"prose"} |
Guess Generation (Exhaustive Search with Coverage Tracking)
Input: $ARGUMENTS
Interpretations
Before executing, identify which interpretation matches the user's input:
Interpretation 1 — Enumerate hidden assumptions: The user has a statement, plan, or claim and wants to exhaustively surface all the implicit guesses and assumptions buried within it.
Interpretation 2 — Generate possibilities for an unknown: The user faces an open question or ambiguity and wants to systematically generate all plausible answers or scenarios.
Interpretation 3 — Stress-test a decision: The user has already made a choice and wants to discover what they might be wrong about by generating alternative readings of their situation.
If ambiguous, ask: "I can help with surfacing hidden assumptions, generating possibilities for an unknown, or stress-testing a decision — which fits?"
If clear from context, proceed with the matching interpretation.
Guess Polarity
Every guess has two properties that affect how it should be weighted downstream in selection. Tag each guess with both.
Direction: Constructive vs Skeptical
| Tag | Meaning | Example |
|---|
| [DIR: CONSTRUCTIVE] | Proposes something to build, try, or act on | "Consolidate the 5 procedures into a single flowchart" |
| [DIR: SKEPTICAL] | Questions whether the premise, approach, or goal is right | "This entire project is overengineering something that works fine" |
| [DIR: DIAGNOSTIC] | Identifies a specific problem or gap without proposing direction | "We don't know if the procedures actually improve outcomes" |
Balance rule: For Interpretation 2 (generate possibilities), aim for at least 40% CONSTRUCTIVE guesses. The natural bias is toward SKEPTICAL — skeptical guesses feel smarter and more "critical thinking." But when someone asks "what should I do next," they need actionable options, not just reasons to doubt. Skeptical guesses are valuable but should not dominate the selection.
Common failure: Selecting mostly skeptical/meta guesses because they have high CRUX ratings. A skeptical guess like "maybe none of this works" will ALWAYS score HIGH on impact-if-wrong, because its assume-wrong branch is "everything changes." This inflates skeptical guesses in selection. Correct for this by evaluating constructive and skeptical guesses in SEPARATE pools before merging.
Purpose: Thinking vs Output
| Tag | Meaning | Example |
|---|
| [USE: THINKING] | Useful for shaping how you approach the problem, but doesn't produce a deliverable | "The value was in the thinking, not the documents" |
| [USE: OUTPUT] | Directly produces something concrete — a file, a plan, an artifact, a decision | "Write a v2 of the configuration that incorporates these procedures" |
| [USE: BOTH] | Informs approach AND produces something | "Have 10 conversations, grade them, build only for observed failures" |
Selection rule: Final selections MUST include at least 3 OUTPUT or BOTH guesses. A selection of all THINKING guesses produces insight without action. A selection of all OUTPUT guesses produces action without insight. Both are needed, but err toward output — the user can think on their own; they're asking you because they want things done.
Assume-Right vs Assume-Wrong Orientation
Some guesses implicitly assume the current approach is RIGHT and extend it. Others assume it's WRONG and redirect.
| Tag | Meaning | Example |
|---|
| [ORIENT: EXTEND] | Builds on the current trajectory | "Integrate the procedures into the existing system" |
| [ORIENT: REDIRECT] | Changes the current trajectory | "Stop building infrastructure; the constraint is now use, not build" |
| [ORIENT: NEUTRAL] | Neither extends nor redirects — orthogonal | "Test before committing either way" |
Balance rule: Selection should include guesses from all three orientations. Over-indexing REDIRECT produces paralysis ("should we even be doing this?"). Over-indexing EXTEND produces tunnel vision. NEUTRAL guesses (tests, experiments, audits) are often the highest-value because they RESOLVE the extend-vs-redirect question.
Core Principles
- GUESSING IS SEARCH - Apply ALL search methods systematically
- GUESSES CREATE THE SPACE - Don't assume pre-existing space; guessing reveals it
- COVERAGE > COUNT - 50 guesses covering 10 dimensions > 500 covering 3 dimensions
- TRACK WHAT'S COVERED - Measure dimensions, perspectives, time horizons, not raw count
- ADAPTIVE DEPTH - Go deep where impact is high and confidence is low
- MINIMUM DEPTH - Generate enough guesses that no reviewer can find gaps
- ONE QUESTION PER GUESS - Never bundle multiple questions into one guess
- CRUX IDENTIFICATION - Mark guesses where ASSUME RIGHT vs ASSUME WRONG produce maximally divergent paths
- QUESTION HIERARCHY - Some questions only asked after others (e.g., exact date after precision level)
- SHOW THE QUESTION - Every guess explicitly states what question it answers
Unbundling Rules
NEVER bundle these into single guesses:
- When + How long (separate: Q1=precision level, Q2=exact date, Q3=duration hours)
- Who + For whom (separate: Q1=who does work, Q2=who benefits)
- Method + Time (separate: Q1=what method, Q2=when applied)
- What + Why (separate: Q1=what is it, Q2=why do it)
Correct structure:
Q1: When do you plan to start? (precision level)
- Within the next hour [CRUX:HIGH]
- Within the next day [CRUX:MED]
- Within the next week [CRUX:MED]
...
Q2: What is the exact start date?
(Only asked after Q1 determines precision)
- [User provides specific date]
- Not yet determined
...
Q3: How long will it take? (duration in hours)
- Less than 1 hour [CRUX:HIGH]
- 1-4 hours [CRUX:MED]
...
CRUX Identification (ARAW Integration)
A entry is CRUX when ASSUME RIGHT leads to completely different actions than ASSUME WRONG.
CRUX Rating Framework
The Test: "If I flip my assumption on this entry, does my ENTIRE approach change?"
| Rating | % of Total | Definition | Test |
|---|
| HIGH | 10-25% | Wrong = solving wrong problem entirely | Strategy completely changes |
| MED | 40-50% | Wrong = significant adjustment needed | Approach changes meaningfully |
| LOW | 30-40% | Wrong = minor adjustment | Details change, core stays same |
HIGH-CRUX Examples (strategy changes)
- "Is this reversible?" - One-way door changes everything
- "Who is the actual decision maker?" - Wrong person = wasted effort
- "Is the stated want the actual want?" - Wrong target entirely
- "Are they in crisis?" - Crisis response vs normal pace
- "Is this the real goal or proxy?" - Solving for wrong level
MED-CRUX Examples (approach changes)
- "How complex is this?" - Changes effort level, not goal
- "What resources are available?" - Constrains options, doesn't change goal
- "What's the timeline precision?" - Shapes approach, doesn't redirect it
LOW-CRUX Examples (details change)
- "Exact number of stakeholders (3 vs 5)" - Scale detail
- "Specific tool choice" - Implementation detail
- "Documentation format" - Output detail
Common Mistakes
- Marking everything HIGH because "it matters"
- Marking HIGH because information is unknown
- Confusing "would be good to know" with "changes everything"
Table Format (with "Why This Rating")
| Entry | CRUX | Why This Rating | ASSUME RIGHT | ASSUME WRONG |
|-------|------|-----------------|--------------|--------------|
| Immediate (now) | HIGH | Crisis mode vs planned = different | Drop everything | Can plan first |
| This week | MED | Near-term changes priority | High priority | Lower priority |
| This month | LOW | Flexible, details change | Standard planning | Adjust timeline |
Ask HIGH-CRUX questions first - they eliminate most uncertainty fastest.
Reference: See /data/guess_libraries/TEMPLATE_unbundled_v2.md for framework.
See /data/guess_libraries/universal/06_why_reason.md for example with correct distribution.
Minimum Depth Requirements
For each method, generate AT LEAST:
| Method | Minimum Per Applicable Category |
|---|
| Morphological (AGENT) | 8+ variations |
| Morphological (ACTION) | 12+ variations |
| Morphological (OBJECT) | 10+ variations |
| Morphological (REASON) | 15+ variations |
| Morphological (METHOD) | 15+ variations |
| Morphological (TIME) | 8+ variations |
| Morphological (DEGREE) | 10+ variations |
| Morphological (CERTAINTY) | 8+ variations |
| Morphological (SCOPE) | 6+ variations |
| Morphological (CONSTRAINTS) | 15+ variations |
| SCAMPER (each operation) | 4+ variations |
| Stakeholder Perspectives | 12+ perspectives |
| Time Horizons | 12+ variations |
| Claim Types (each) | 4+ variations |
| Analogy Domains (each) | 4+ variations |
| Pre-Mortem (each error type) | 2+ variations |
Total minimum: 200+ guesses for any meaningful input
Reference: See /docs/example_comprehensive_guess_generation.md for a complete example with 238 guesses.
Derivation Requirement
Every guess must show derivation:
[D: from morphological AGENT dimension][D: from SCAMPER Substitute operation][D: from analogy to biology domain][D: from pre-mortem perception error check]
Do NOT list guesses without showing which method generated them.
Step 0: Check Guess Library First
Before generating guesses from scratch, check if a pre-generated library exists:
python scripts/guess_library.py lookup "$INPUT"
If library found:
- Retrieve with:
python scripts/guess_library.py get [library_id]
- Review the 200+ pre-generated guesses
- Customize for this specific user if needed
- Skip to Step 13 (Coverage Analysis)
If no library found:
- Continue with full generation below
- After completing, save to library with:
python scripts/guess_library.py add
Related goals: Check for related goal chains that share guesses:
python scripts/guess_library.py related [library_id]
Step 0.5: Select Coverage Mode
Choose based on space size (from /spd or estimated):
| Mode | When to Use | What It Does |
|---|
| EXHAUSTIVE | Stakes high, space small | All methods, all dimensions |
| TARGETED | Time-constrained, space large | High-impact regions only |
| ADAPTIVE | Uncertain stakes | Start broad, go deep on signal |
| BOUNDARY | New/unknown problem | Map edges before interior |
Selected mode: [MODE]
Reason: [why this mode fits]
Step 1: Filter Non-Guesses
| Type | Test | Action |
|---|
| Definition | About words | Accept |
| Technique | Method | Accept |
| Category | Classification | Accept |
| Question | Requesting | Answer |
| Command | Directing | Execute |
Non-guesses: [list]
Step 2: Parse Surface Claims
Extract ALL claims (aim for 10-20 per sentence):
- Explicit claims (stated directly)
- Implicit claims (assumed but not stated)
- Presupposition claims (must be true for statement to make sense)
- Implicature claims (conversationally implied)
Surface claims extracted: [list]
Step 3: Depth Decision (Per Claim)
For each claim, decide depth before exploring:
| Claim | Impact if Wrong | Confidence | Depth Decision |
|---|
| [claim 1] | HIGH/MED/LOW | HIGH/MED/LOW | DEEP/SHALLOW |
| [claim 2] | HIGH/MED/LOW | HIGH/MED/LOW | DEEP/SHALLOW |
Depth rules:
- HIGH impact + LOW confidence → DEEP (full unbundling, all inversions, analogy search)
- HIGH impact + HIGH confidence → MEDIUM (verify assumptions)
- LOW impact + any confidence → SHALLOW (note and move on, 1-2 unbundlings max)
Step 4: Morphological Analysis
Dimension Enumeration (Track Coverage)
| Dimension | Applicable? | Values Enumerated | Covered? |
|---|
| AGENT (who) | YES/NO | [values] | ✓/✗ |
| ACTION (what) | YES/NO | [values] | ✓/✗ |
| OBJECT (affected) | YES/NO | [values] | ✓/✗ |
| REASON (why) | YES/NO | [values] | ✓/✗ |
| METHOD (how) | YES/NO | [values] | ✓/✗ |
| TIME (when) | YES/NO | [values] | ✓/✗ |
| LOCATION (where) | YES/NO | [values] | ✓/✗ |
| DEGREE (how much) | YES/NO | [values] | ✓/✗ |
| CERTAINTY (how sure) | YES/NO | [values] | ✓/✗ |
| SCOPE (how broadly) | YES/NO | [values] | ✓/✗ |
Dimension coverage: [N] / 10 dimensions covered
Step 5: SCAMPER Transformations (Track Coverage)
| Operation | Applied? | Variations Generated |
|---|
| S - Substitute | ✓/✗ | [count] |
| C - Combine | ✓/✗ | [count] |
| A - Adapt | ✓/✗ | [count] |
| M - Modify | ✓/✗ | [count] |
| P - Put to other use | ✓/✗ | [count] |
| E - Eliminate | ✓/✗ | [count] |
| R - Reverse | ✓/✗ | [count] |
SCAMPER coverage: [N] / 7 operations applied
Step 6: Perspective Coverage (Stakeholders)
| Stakeholder | Considered? | Guesses from This View |
|---|
| Speaker/user | ✓/✗ | [count] |
| Direct beneficiaries | ✓/✗ | [count] |
| Direct losers | ✓/✗ | [count] |
| Implementers | ✓/✗ | [count] |
| Future selves | ✓/✗ | [count] |
| Adversaries | ✓/✗ | [count] |
Perspective coverage: [N] stakeholders considered
Step 7: Time Horizon Coverage
| Horizon | Considered? | Guesses from This Frame |
|---|
| Immediate (now) | ✓/✗ | [count] |
| Short-term | ✓/✗ | [count] |
| Medium-term | ✓/✗ | [count] |
| Long-term | ✓/✗ | [count] |
| Historical | ✓/✗ | [count] |
Time coverage: [N] / 5 horizons covered
Step 8: Inversion Coverage
For each surface claim:
| Claim | Assume-Right Explored? | Assume-Wrong Explored? |
|---|
| [claim 1] | ✓/✗ | ✓/✗ |
| [claim 2] | ✓/✗ | ✓/✗ |
Inversion coverage: [N]% of claims have both branches
Step 9: Claim Type Coverage
| Type | Guesses Generated? | Count |
|---|
| Factual | ✓/✗ | [N] |
| Causal | ✓/✗ | [N] |
| Predictive | ✓/✗ | [N] |
| Normative | ✓/✗ | [N] |
| Modal | ✓/✗ | [N] |
| Relational | ✓/✗ | [N] |
| Intentional | ✓/✗ | [N] |
| Meta | ✓/✗ | [N] |
Type coverage: [N] / 8 types represented
Step 10: Analogy Search (10 Domains)
| Domain | Searched? | Analogies Found |
|---|
| Biology | ✓/✗ | [guesses] |
| Physics | ✓/✗ | [guesses] |
| Economics | ✓/✗ | [guesses] |
| Psychology | ✓/✗ | [guesses] |
| Engineering | ✓/✗ | [guesses] |
| Military | ✓/✗ | [guesses] |
| Nature | ✓/✗ | [guesses] |
| Games | ✓/✗ | [guesses] |
| History | ✓/✗ | [guesses] |
| Medicine | ✓/✗ | [guesses] |
Analogy coverage: [N] / 10 domains searched
Step 11: Unbundling (Deep for DEEP claims only)
For DEEP claims, apply all unbundling patterns:
Patterns to apply:
- "I [verb]" → 6 hidden guesses
- "[noun] is [adjective]" → 7 hidden guesses
- "because [reason]" → 7 hidden guesses
- "want/need" → 7 hidden guesses
- "improve/better/good" → 7 hidden guesses
- "system" → 7 hidden guesses
For SHALLOW claims, apply 1-2 patterns only.
Unbundling done: [summary]
Step 12: Pre-Mortem (15 Error Types)
For key claims, check each error type:
| Error Type | Checked? | Finding |
|---|
| Perception error | ✓/✗ | [guess if applicable] |
| Memory error | ✓/✗ | [guess if applicable] |
| Interpretation error | ✓/✗ | [guess if applicable] |
| Source error | ✓/✗ | [guess if applicable] |
| Selection bias | ✓/✗ | [guess if applicable] |
| Confirmation bias | ✓/✗ | [guess if applicable] |
| Availability bias | ✓/✗ | [guess if applicable] |
| Anchoring | ✓/✗ | [guess if applicable] |
| Motivated reasoning | ✓/✗ | [guess if applicable] |
| Social pressure | ✓/✗ | [guess if applicable] |
| False dichotomy | ✓/✗ | [guess if applicable] |
| Scope error | ✓/✗ | [guess if applicable] |
| Timing error | ✓/✗ | [guess if applicable] |
| Causation error | ✓/✗ | [guess if applicable] |
| Definition error | ✓/✗ | [guess if applicable] |
Pre-mortem coverage: [N] / 15 error types checked
Step 13: Space Created vs Space Covered
Space Created (by guessing)
Dimensions discovered: [list]
Regions identified: [list clusters of guesses]
Boundaries found: [edges of the space]
Space Coverage Analysis
COVERAGE METRICS SUMMARY:
├── Dimensions: [N]/10 covered ([%])
├── SCAMPER: [N]/7 operations ([%])
├── Perspectives: [N] stakeholders
├── Time horizons: [N]/5 ([%])
├── Inversion: [N]% of claims both branches
├── Claim types: [N]/8 ([%])
├── Analogies: [N]/10 domains ([%])
├── Pre-mortem: [N]/15 errors ([%])
└── OVERALL: [weighted average]%
GAPS IDENTIFIED:
├── Uncovered dimensions: [list]
├── Missing perspectives: [list]
├── Missing time horizons: [list]
├── Claims without inversion: [list]
├── Missing claim types: [list]
└── Unsearched domains: [list]
Step 14: Fill Gaps or Justify Skipping
For each gap identified:
| Gap | Action | Reason |
|---|
| [gap 1] | FILL / SKIP | [if skip: why it's OK to skip] |
| [gap 2] | FILL / SKIP | [if skip: why it's OK to skip] |
Strategic skips (justified under-coverage):
Gaps filled: [list guesses added to fill gaps]
Step 15: Confidence × Impact Matrix
Plot all guesses:
HIGH IMPACT IF WRONG
│
┌───────────────────────┼───────────────────────┐
│ │ │
│ INVESTIGATE │ CRITICAL │
│ (worth checking) │ (must verify) │
│ │ │
LOW ├───────────────────────┼───────────────────────┤ HIGH
CONF│ │ │ CONF
│ ACKNOWLEDGE │ TRUST │
│ (note uncertainty) │ (probably true) │
│ │ │
└───────────────────────┼───────────────────────┘
│
LOW IMPACT IF WRONG
Critical guesses (High Impact × Low Confidence): [list]
Output Format
## INPUT PARSED
[original input]
## COVERAGE MODE
Mode: [EXHAUSTIVE/TARGETED/ADAPTIVE/BOUNDARY]
Reason: [why]
## DEPTH DECISIONS
[table of claims with DEEP/SHALLOW assignments]
## GUESSES GENERATED
[organized by method: morphological, SCAMPER, analogy, inversion, unbundling, pre-mortem]
## COVERAGE METRICS
Dimensions: [N]/10 ([%])
SCAMPER: [N]/7 ([%])
Perspectives: [N] stakeholders
Time horizons: [N]/5 ([%])
Inversion: [N]%
Claim types: [N]/8 ([%])
Analogies: [N]/10 ([%])
Pre-mortem: [N]/15 ([%])
OVERALL: [%]
## GAPS
Identified: [list]
Filled: [list]
Justified skips: [list with reasons]
## SPACE ANALYSIS
Space created: [dimensions discovered, regions identified]
Space covered: [%]
Blind spots: [any remaining]
## CRITICAL GUESSES
[High Impact × Low Confidence - must question these]
## POLARITY BALANCE
Constructive: [N] ([%])
Skeptical: [N] ([%])
Diagnostic: [N] ([%])
Output: [N] | Thinking: [N] | Both: [N]
Extend: [N] | Redirect: [N] | Neutral: [N]
## TOTAL
Guesses: [N]
Coverage: [%]
Execution Checklist
Before completing, verify:
Next Procedure
→ INVOKE: /qag [CRITICAL guesses]
Execute now: Generate guesses with full coverage tracking.
