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pantheon-ai/frame-problem

Classify a problem using Cynefin triangulation before acting — routes to the right skill chain (investigate, brainstorm, probe, troubleshoot).

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frame-problem-to-experiment-llm.mdreferences/

domain:
chaotic
verb:
act
constraint-type:
absent
problem:
{problem statement from classification}
scale:
-

Frame-Problem to Experiment Handoff

Thinking Trail

  • Considered: {what approaches were weighed during framing}
  • Rejected: {why structured domains didn't fit — constraints are absent}
  • Surprised by: {chaos signals — urgency, incoherence, novel disruption}
  • Triangulation: T1={Keogh level}, T2={predictability}, T3={disassembly} — {convergence}
  • Models used: Cynefin triangulation (Keogh + Predictability + Disassembly)
  • Constraints discovered: None — that's the point. Constraints are absent.

Decisions

  1. Domain: Chaotic (absent constraints — crisis or deliberate disruption)
  2. Route: experiment → stabilize → frame-problem
  3. Rationale: {no analysis possible — must act first to impose minimal structure}

Actions Taken

  • Classified via Q1: absent constraints identified
  • Scale: not applicable (Chaotic bypasses scale assessment)

Output

🎯 Chaotic → Act → /experiment → stabilize → /frame-problem | OpenSpec: no

Domain Transition

From: Confused → To: Chaotic Constraint shift: unknown → absent. No cause-effect relationships visible. Must act to impose minimal constraints before any analysis is possible.

For /experiment

  • Chaos type assessment: Determine accidental (crisis — something broke) vs deliberate (innovation — intentionally disrupting)
  • Initial action: {first safe action to impose minimal structure}
  • Gate requirement: Human gates after EVERY action — human IS the constraint
  • Exit watch: Look for emerging structure → transition to probe when patterns appear
  • Do NOT: Attempt analysis or planning — act first, sense second

Accumulated Context

Token guidance: target 300 tokens inline. For depth, use references — point to thinking artifact files rather than embedding full content. Soft cap: 600 tokens inline per handoff. If you need more, move detail to a knowledge file and reference it. Accumulated cap: 800 tokens across a chain — compress to 200 at cap (keep: decisions, constraints, rejected paths). References to thinking files do NOT count toward the cap.

references

frame-problem-to-brainstorm-llm.md

frame-problem-to-experiment-llm.md

frame-problem-to-investigate-llm.md

frame-problem-to-probe-liminal-llm.md

frame-problem-to-probe-llm.md

frame-problem-to-troubleshoot-llm.md

SKILL.md

tile.json