shinpr Context: Drive the feedback loop by reflecting on outcomes, updating target artifacts, and distilling learnings across the knowledge pyramid (see product-principles skill for Tier definitions).
Required Skills [LOAD BEFORE EXECUTION]
- [LOAD IF NOT ACTIVE]
product-principles— Knowledge Pyramid and promotion criteria - [LOAD IF NOT ACTIVE]
hypothesis-discipline— validation results, lifecycle status, and confidence changes
Delegate Level 2 and Level 3 distillation to knowledge-distiller for independent evidence synthesis.
Execution Decision Flow
1. Scope Assessment
Input: Use the path or text supplied with the explicit skill invocation. If no input was supplied and the target cannot be inferred unambiguously, ask for it.
Determine the reflection level (see references/reflection-guide.md):
| Trigger | Level | Target Files |
|---|---|---|
| Hypothesis concluded | Level 1: Hypothesis | The hypothesis file |
| Multiple hypotheses concluded under an Opportunity | Level 2: Opportunity | Opportunity file (Tier 2 Learnings section) |
| PRD delivered, quarterly review, strategic pivot | Level 3: Vision | docs/product/vision.md, docs/product/learnings.md |
2. Result Recording
Level 1: Hypothesis Reflection
- Verify the hypothesis file has been updated with results (validation results, confidence scores, evidence)
- Document a learning when the result changes the parent Opportunity or a later decision
- Check if this result changes understanding of the parent Opportunity
Level 2: Opportunity Reflection
- Start from the Opportunity and load the hypothesis evidence needed to assess candidate learnings and contradictions
- Prepare context for knowledge-distiller (hypothesis summaries, results, confidence changes)
Level 3: Vision Reflection
- Gather the cross-Opportunity evidence needed for the outcome, NSM, or Tier 1 decision
- Review Product Outcomes — are targets still correct?
- Review NSM — still the right connecting metric?
- Prepare context for knowledge-distiller
3. Knowledge Distillation
Invoke knowledge-distiller for evidence distillation:
- knowledge-distiller operates in a separate context to avoid individual hypothesis bias
- It distills evidence into candidate learnings and contradictions
- It proposes Tier 2 learnings (for Opportunity) or Tier 1 learnings (for Vision)
- It enforces distillation quality criteria (per product-principles skill)
Present distillation results to the user for the knowledge-promotion decision:
- Candidate learnings with proposed tiers, supporting evidence, and contexts
- Contradictions found and the decisions they may affect
End the current turn with the distillation result as the workflow output. Promote knowledge only after the user confirms the proposal in a later turn.
4. Knowledge Promotion
After that confirmation:
Tier 3 → Tier 2
- Write learnings to the Opportunity file's "Tier 2 Learnings" section
- Include hypothesis references that support each learning
Tier 2 → Tier 1
- Write to
docs/product/learnings.md - Include supporting evidence references and their dates
- State the contexts where the learning applies
Sub-agent Usage
| Agent | When | Why (context separation benefit) |
|---|---|---|
| knowledge-distiller | Level 2 and Level 3 reflection | Independent evidence synthesis across hypotheses |
Scope Boundaries
Included: Result recording, knowledge distillation, and Tier promotion Not included: Hypothesis validation (→ recipe-validate), new hypothesis generation (→ recipe-discover)
Completion
The workflow is complete when approved promotions are updated, or a no-change result is reported with the evidence and contradictions relevant to the decision.