Frame
Sense-make → triangulate → decompose if needed → route. Domain determines agent pattern, not just skill.
Framing: $ARGUMENTS
⚠️ AskUserQuestion Guard
CRITICAL: After EVERY AskUserQuestion call, check if answers are empty/blank. Known Claude Code bug: outside Plan Mode, AskUserQuestion silently returns empty answers without showing UI.
If answers are empty: DO NOT proceed with assumptions. Instead:
- Output: "⚠️ Questions didn't display (known Claude Code bug outside Plan Mode)."
- Present the options as a numbered text list and ask user to reply with their choice number.
- WAIT for user reply before continuing.
0. Auto-classify (skip if no $ARGUMENTS)
Read $ARGUMENTS. Attempt domain classification using constraint language.
If confidence ≥80%: Propose — but ALWAYS run the Adjacent Domain Challenge before confirming:
🎯 Auto-classified: [Domain] (constraint: [type])
→ Verb: [probe|analyze|execute|act|decompose]
→ Suggested route: [skill chain]
⚖️ Adjacent challenge: What if this is actually [nearest domain]?
[1-2 sentence argument for why it could be the adjacent domain]
[Why the original classification still holds — or doesn't]
Confirm? [Yes / Re-classify manually]
LLM bias warning: You are systematically biased toward Complicated (you have "expert knowledge" for everything, so you see governing constraints everywhere). When auto-classifying as Complicated, actively look for signs it might be Complex: Would two experts disagree? Is there genuine novelty? Has this specific combination been tried before?
If confidence <80% or no $ARGUMENTS: Skip to Step 1 (triangulation).
1. Triangulate (3 tests)
Do NOT ask user to self-classify by constraint type — people systematically misclassify. Instead, ask 3 concrete questions they CAN answer accurately.
Question Refinement: If $ARGUMENTS is vague or broad, generate 2-3 clarifying sub-questions to sharpen the problem statement. Present them inline before proceeding.
AskUserQuestion — all applicable questions in one call:
T1 — "Who's done this before?" (Keogh Scale)
- 1️⃣ Everyone on the team knows how → Clear
- 2️⃣ Someone on our team / we have access to expertise → Complicated
- 3️⃣ Someone outside our org has, but not us → Complex
- 4️⃣ Nobody has ever done this → Complex (near Chaotic)
- 5️⃣ Can't even tell what "this" is → Confused
T2 — "Same inputs, same result?" (Predictability)
- 🔁 Yes, reliably → Ordered (Clear or Complicated)
- 🎲 Probably not — path-dependent, sensitive to context → Unordered (Complex)
- 💥 No relationship between action and outcome → Chaotic
T3 — "Can you take it apart?" (Disassembly)
- 🔧 Yes — independent pieces, reassemble identically → Complicated max
- 🧬 No — entangled, changing parts changes the whole → Complex min
- ➗ Some parts yes, some parts no → Composite (→ Step 1.5 decompose)
Also ask:
Q-Scale (skip if Chaotic):
- 🪨 Boulder (multi-step, ambiguous, architectural)
- 🫧 Pebble (single file, obvious implementation)
- ❓ Not sure
Q-Complicated sub (only if T1=2 AND T2=ordered):
- 📈 Evolving — system improving, growing capacity →
investigate - 📉 Degraded — was working, now failing →
troubleshoot - ↔️ Both — improving in one dimension, degrading in another →
investigatewithtroubleshootsub-task
Triangulation Logic
All 3 agree → High confidence. Classify directly.
2 of 3 agree → Classify by majority. Note the dissenting signal — it may indicate a liminal (boundary) state. Present:
🎯 [Domain] (2/3 tests agree)
⚠️ Liminal signal: T[N] suggests [adjacent domain] — [what this means]
All 3 disagree or T3=composite → Problem spans multiple domains. Go to Step 1.5.
Misclassification traps to watch for:
- Engineers/experts picking T1=2 + T2=ordered when T3=entangled → likely Complex, not Complicated (expertise bias)
- Overwhelm picking T2=chaotic when it's actually Complex with enabling constraints → slow down, decompose
- "Nobody has done this" + "predictable result" = contradiction → decompose, parts are in different domains
1.5. Decompose (only if tests disagree or problem is composite)
When triangulation doesn't converge, the problem is too coarse. Snowden's rule: "If you can't agree on it, break it down until you can."
- Break $ARGUMENTS into 2-4 sub-problems
- For each sub-problem, apply the triangulation tests mentally (don't re-ask user — use context)
- Present a domain map:
🧩 Composite problem — sub-parts in different domains:
├── [sub-problem 1]: [Domain] → [verb] → [skill]
├── [sub-problem 2]: [Domain] → [verb] → [skill]
└── [sub-problem 3]: [Domain] → [verb] → [skill]
Suggested sequence: [order based on dependencies + risk]
Start with [highest-risk/Complex parts first — that's where value and risk concentrate]
AskUserQuestion: "Does this decomposition match your understanding? Adjust / Confirm / Re-frame"
2. Classify + Route
Map triangulation result → domain → verb → skill chain:
| Domain | Constraint | Verb | Scale | Route | OpenSpec? |
|---|---|---|---|---|---|
| Clear | Rigid | execute | Pebble | Just code it | No |
| Clear | Rigid | execute | Boulder | openspec-develop directly |
Yes |
| Complicated | Governing/Evolving | analyze | Any | investigate → openspec-plan |
Boulder: yes |
| Complicated | Governing/Degraded | analyze | Any | troubleshoot → stabilize → re-frame |
No |
| Complicated | Governing/Both | analyze | Any | investigate + troubleshoot sub-task |
Boulder: yes |
| Complex | Enabling/no hypothesis | probe | Any | brainstorm → probe → openspec-plan |
Yes |
| Complex | Enabling/has hypothesis | probe | Any | probe → sense → openspec-plan |
Yes |
| Liminal Comp↔Complex | Mixed | probe+analyze | Any | probe first (resolve boundary) → re-frame |
No |
| Chaotic | Absent | act | — | experiment → stabilize → frame-problem |
No |
| Confused | Unknown | decompose | Any | Step 1.5 if not done, else ask user for more context | — |
| Composite | Mixed | per sub-problem | Mixed | Parallel/sequential per domain map from 1.5 | Per part |
For single-domain result, present:
🎯 [Domain] → [Verb] → [skill chain] | OpenSpec: [yes/no] | Scale: [boulder/pebble]
For composite result, present the domain map from Step 1.5 with full routing.
3. Handoff
AskUserQuestion "Proceed?": Start chain / Re-frame / Skip framing.
On confirm → invoke first skill with $ARGUMENTS (or first sub-problem for composite).
When to Use
- The problem statement is vague, contradictory, or solution-shaped ("we need a microservice").
- The team disagrees on what the problem actually is or what success looks like.
- A previous attempt at solving something failed despite correct execution — the framing may have been wrong.
- You are unsure which skill or approach to apply next (unsure whether to investigate, probe, troubleshoot, or experiment).
- The scope of a request is unclear: could be a pebble or a boulder, could be one domain or several.
When Not to Use
- The task is fully specified and unambiguous — just execute it.
- You already know the Cynefin domain and the next skill to invoke.
- The problem is a simple bug with a clear reproduction path — go directly to
troubleshoot. - The user has explicitly asked to skip framing and proceed to a named skill.
- Time is critical and the domain is Chaotic — act first, frame later.
Anti-Patterns
- NEVER frame the problem as a solution — "We need a microservice" is not a problem statement. Why: Solution-framed problems foreclose better options; reframe as "We need to reduce deployment coupling."
- NEVER skip domain classification — Jumping straight to a solution approach without classifying the domain applies the wrong strategy. Why: Clear domain problems need best practices; Complex domain problems need probes; mixing these causes failure.
- NEVER accept the user's first framing at face value — Initial problem statements are often symptoms. Why: The real constraint or goal is usually one "why?" deeper; accepting the surface framing wastes effort.
- NEVER classify as Complicated just because you have knowledge — LLMs have expert-level knowledge on nearly everything and will over-index on Complicated. Why: This systematically bypasses the probe/experiment path that Complex problems require, leading to confident but wrong solutions.
- NEVER skip the Adjacent Domain Challenge when auto-classifying — A single-domain verdict without challenging the nearest boundary is premature. Why: Liminal problems handled with the wrong verb (analyze vs. probe) consistently fail at the boundary.
Usage Examples
Reframing a vague bug report:
# Input: "The dashboard is slow"
# Skill probes: What is slow? Under what conditions? For which users?
# Output: "Dashboard queries >10s for accounts with >1000 records (Complicated domain)"
Classifying a new feature request:
# Input: "Add AI recommendations to the product page"
# Skill classifies: Complex domain (unknown user behavior, emergent)
# Routes to: probe skill for safe-to-fail experiment design
Decomposing a composite problem:
# Input: "Migrate our monolith to microservices and fix the checkout bug"
# Skill decomposes:
# - Checkout bug: Complicated/Degraded → troubleshoot
# - Monolith migration: Complex → brainstorm → probe → openspec-plan
# Routes to: troubleshoot first (lower risk, unblocks Complex work)
References
- Frame → Brainstorm — handoff template: Complex, no hypothesis → brainstorm
- Frame → Probe — handoff template: Complex, has hypothesis → probe
- Frame → Probe (Liminal) — handoff template: Liminal Complicated↔Complex → probe
- Frame → Investigate — handoff template: Complicated, evolving → investigate
- Frame → Troubleshoot — handoff template: Complicated, degraded → troubleshoot
- Frame → Experiment — handoff template: Chaotic → experiment