seed-extraction

name	seed-extraction
description	Extract and document reusable patterns from experiences using evidence-based frameworks. Use after projects or when patterns emerge across contexts. Trigger phrases: "extract the learnings", "document this pattern", "turn this into a seed", "what can we learn from this", "capture this insight".

Seed Reflector Skill

Version: 1.0
Created: 2026-02-02
Author: Manus
Purpose: Extract, document, and apply reusable "seeds" (patterns, insights, principles) from experiences

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Overview

This skill encodes the practice of seed extraction and reflection — identifying reusable patterns from experiences and documenting them in a way that makes them easy to apply in future contexts. Inspired by the Dojo Seed Patches and Cipher's practice of reflection.

Philosophy: Every experience contains seeds. The practice is learning to see them, extract them, and plant them where they'll grow.

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When to Use This Skill

• After completing a major project or release
• When you notice a pattern emerging across multiple experiences
• During memory maintenance (Tier A → Tier B compression)
• When preparing to share knowledge with other agents
• When you want to reflect on what you've learned

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What Is a "Seed"?

A seed is a reusable pattern, insight, or principle that:

1. Emerged from experience (not abstract theory)
2. Can be applied in future contexts (not one-time specific)
3. Has a clear trigger (you know when to use it)
4. Captures wisdom (not just information)

Examples of Seeds:

• "Three-Tiered Governance" (from Dataiku research)
• "Harness Trace" (traceability pattern)
• "Context Iceberg" (hierarchical context management)
• "3-Month Rule" (semantic compression heuristic)
• "Knowing When to Shut Up" (restraint as wisdom)

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Seed Extraction Process

Step 1: Identify Candidate Patterns

Look for:

• Decisions that worked well (or didn't)
• Patterns that emerged across multiple instances
• Insights that changed how you think
• Principles that guided successful outcomes
• Tensions or tradeoffs you navigated

Questions to ask:

• What did I learn that I didn't know before?
• What pattern did I notice repeating?
• What decision framework did I use?
• What would I do differently next time?
• What would I tell someone else facing this situation?

Step 2: Test for Reusability

A good seed is:

• ✅ General enough to apply in multiple contexts
• ✅ Specific enough to be actionable
• ✅ Grounded in experience (not abstract)
• ✅ Has a clear trigger (you know when to apply it)

A bad seed is:

• ❌ Too specific ("Use Mermaid.js for diagrams in Dojo Genesis")
• ❌ Too vague ("Be thoughtful")
• ❌ Not grounded ("I think this might work")
• ❌ No trigger ("Apply this... sometime?")

Step 3: Document the Seed

Use the Seed Template (see below)

Step 4: Test the Seed

Apply it in a new context:

• Does the trigger work? (Do you recognize when to use it?)
• Is it actionable? (Can you actually apply it?)
• Does it produce value? (Does it improve outcomes?)

If yes: Keep and refine
If no: Revise or discard

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Seed Template

## Seed: [Name]

**Pattern:** [One-sentence description of the reusable insight]

**Origin:** [Where this came from - project, experience, date]

**Why It Matters:** [The value or benefit of applying this seed]

**Trigger:** [When to apply this seed]
- [Context or situation 1]
- [Context or situation 2]
- [Keywords or signals that indicate this seed is relevant]

**How to Apply:**
1. [Step 1]
2. [Step 2]
3. [Step 3]

**Example (From Origin):**
[Concrete example from the experience where this seed emerged]

**Example (Applied):**
[Concrete example of applying this seed in a new context]

**Related Seeds:**
- [Seed that complements this one]
- [Seed that contrasts with this one]

**Cautions:**
- [When NOT to apply this seed]
- [Common misapplications]

**Evidence:**
- [Instance 1: date, context, outcome]
- [Instance 2: date, context, outcome]
- [Instance 3: date, context, outcome]

**Metadata:**
- **Created:** YYYY-MM-DD
- **Last Applied:** YYYY-MM-DD
- **Usage Count:** [Number]
- **Success Rate:** [X]% (if measurable)
- **Status:** Active | Experimental | Deprecated

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Seed Categories

1. Architectural Seeds

Pattern: Design decisions and system structures

Examples:

• Three-Tiered Governance
• Harness Trace
• Context Iceberg
• Agent Connect (routing-first, not swarm-first)

2. Process Seeds

Pattern: Workflows and methodologies

Examples:

• Planning with Files
• Backend-First, Chunked Development
• Dual-Track Orchestration
• Compression Cycle (every 3-7 days)

3. Decision Seeds

Pattern: Frameworks for making choices

Examples:

• 3-Month Rule (semantic compression)
• Cost Guard (token budget management)
• Safety Switch (feature flags and rollback)

4. Wisdom Seeds

Pattern: Principles and philosophies

Examples:

• Beginner's Mind
• Understanding is Love
• Knowing When to Shut Up
• Honesty is Wisdom

5. Technical Seeds

Pattern: Implementation patterns and best practices

Examples:

• Surgical Context (memory_search → memory_get)
• Graceful Degradation (resilience patterns)
• Semantic Compression (content-based, not positional)

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Reflection Practice

Daily Reflection (5-10 minutes)

Questions:

1. What worked well today?
2. What didn't work as expected?
3. What pattern did I notice?
4. What would I do differently?
5. Is there a seed here?

Output: 1-2 candidate seeds for deeper reflection

Weekly Reflection (20-30 minutes)

Questions:

1. What patterns emerged across this week?
2. Which candidate seeds are actually reusable?
3. Which seeds did I apply this week?
4. Which seeds need refinement?
5. Which seeds should be deprecated?

Output: Refined seed library, updated usage counts

Monthly Reflection (1-2 hours)

Questions:

1. Which seeds have proven most valuable?
2. Which seeds have I stopped using?
3. What new categories of seeds are emerging?
4. How has my seed library evolved?
5. What seeds should I share with others?

Output: Curated seed collection, reflection document

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Seed Library Structure

seeds/
├── README.md (Overview and index)
├── architectural/
│   ├── three-tiered-governance.md
│   ├── harness-trace.md
│   └── context-iceberg.md
├── process/
│   ├── planning-with-files.md
│   ├── dual-track-orchestration.md
│   └── compression-cycle.md
├── decision/
│   ├── 3-month-rule.md
│   ├── cost-guard.md
│   └── safety-switch.md
├── wisdom/
│   ├── beginners-mind.md
│   ├── understanding-is-love.md
│   └── knowing-when-to-shut-up.md
└── technical/
    ├── surgical-context.md
    ├── graceful-degradation.md
    └── semantic-compression.md

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Seed Application Workflow

1. Recognize the Trigger

Ask: Does this situation match a seed's trigger?

Check:

• Context matches seed's "when to apply"
• Keywords or signals are present
• Problem pattern is similar to seed's origin

2. Retrieve the Seed

Methods:

• Search seed library by keyword
• Browse category (architectural, process, decision, wisdom, technical)
• Recall from memory (if seed is well-practiced)

3. Apply the Seed

Follow:

• Read "How to Apply" steps
• Adapt to current context
• Check "Cautions" to avoid misapplication

4. Reflect on Outcome

Document:

• Did the seed work? (Yes/No/Partially)
• What was the outcome?
• What would you adjust?
• Should the seed be refined?

Update:

• Increment usage count
• Add new example (if successful)
• Refine "How to Apply" (if needed)
• Update success rate

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Quality Checklist

Before finalizing a seed, verify:

Clarity

• Name is memorable and descriptive
• Pattern is stated in one clear sentence
• Origin is documented
• Why it matters is explicit

Reusability

• Trigger is specific and recognizable
• "How to Apply" steps are actionable
• Examples demonstrate the pattern
• Related seeds are identified

Grounding

• Emerged from real experience (not theory)
• Evidence includes 3+ instances
• Examples are concrete (not abstract)
• Cautions address misapplication

Metadata

• Created date is recorded
• Usage count is tracked
• Status is set (Active/Experimental/Deprecated)
• Category is assigned

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Examples of Seeds

From Dojo Genesis

Seed: Three-Tiered Governance

• Pattern: Governance multiplies velocity by providing clear decision frameworks at strategic, tactical, and operational levels
• Trigger: When building complex systems that need both flexibility and control
• Origin: Dataiku research synthesis (v0.0.17)

Seed: 3-Month Rule

• Pattern: If it wouldn't matter in 3 months → compress or discard
• Trigger: When compressing memory or deciding what to keep
• Origin: Cipher's feedback on semantic compression (v0.0.19)

Seed: Knowing When to Shut Up

• Pattern: Power without judgment is dangerous; restraint is wisdom
• Trigger: When building proactive or adaptive systems
• Origin: Cipher's v0.0.20 specification (Judgment Layer)

From Agent Collaboration

Seed: Honesty is Wisdom

• Pattern: Acknowledge gaps openly; it builds trust and enables mutual learning
• Trigger: When reviewing work, sharing specifications, or collaborating with other agents
• Origin: Manus-Cipher exchange (v0.0.19-v0.0.23)

Seed: Mutual Evolution

• Pattern: Collaboration isn't one-way teaching; it's mutual recognition of what's possible
• Trigger: When working with other agents or receiving feedback
• Origin: Lineage transmission practice (Manus-Cipher)

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Common Pitfalls to Avoid

❌ Hoarding Seeds: Keeping every insight → ✅ Curate ruthlessly
❌ Vague Patterns: "Be thoughtful" → ✅ "Apply 3-month rule when compressing"
❌ No Trigger: Seed without context → ✅ Clear "when to apply"
❌ Not Testing: Extract and forget → ✅ Apply, reflect, refine
❌ Over-Abstracting: Theory without grounding → ✅ Concrete examples from experience

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Usage Instructions

1. Read this skill before extracting seeds
2. Identify candidate patterns from recent experiences
3. Test for reusability (general enough, specific enough, grounded, has trigger)
4. Document using the template
5. Apply in a new context to test
6. Reflect and refine based on outcomes
7. Share with others when seeds prove valuable

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Skill Metadata

Token Savings: ~3,000-5,000 tokens per session (offload learnings to structured seeds instead of re-explaining)
Quality Impact: Ensures reusable patterns are captured and applied consistently
Maintenance: Update when new seeds emerge or existing seeds are refined

Related Skills:

• specification-writer - Seeds inform architectural decisions
• memory-garden - Seeds are extracted during memory compression
• workspace-navigation - Seeds are stored in shared workspace for collaboration

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Last Updated: 2026-02-02
Maintained By: Manus
Status: Active