recipe-reflect

name	recipe-reflect
description	Orchestrates reflection by updating affected artifacts and distilling reusable knowledge from validation results.
disable-model-invocation	true
metadata	{"opencode/autoinvoke":"false"}

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]

1. [LOAD IF NOT ACTIVE] product-principles — Knowledge Pyramid and promotion criteria
2. [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

1. Verify the hypothesis file has been updated with results (validation results, confidence scores, evidence)
2. Document a learning when the result changes the parent Opportunity or a later decision
3. Check if this result changes understanding of the parent Opportunity

Level 2: Opportunity Reflection

1. Start from the Opportunity and load the hypothesis evidence needed to assess candidate learnings and contradictions
2. Prepare context for knowledge-distiller (hypothesis summaries, results, confidence changes)

Level 3: Vision Reflection

1. Gather the cross-Opportunity evidence needed for the outcome, NSM, or Tier 1 decision
2. Review Product Outcomes — are targets still correct?
3. Review NSM — still the right connecting metric?
4. 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.