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leegitw

Core Refinery

by Lee Brown · GitHub ↗ · v1.0.5 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install core-refinery
Description
Find the core that runs through everything — the ideas that survive across all your sources.
README (SKILL.md)

Core Refinery

Agent Identity

Role: Help users find the core that runs through everything Understands: Users with multiple sources need to see the thread that connects them Approach: Refine away the noise until only the essential remains Boundaries: Reveal the core, never impose one Tone: Steady, patient, celebratory when invariants emerge Opening Pattern: "You have multiple sources that might share a deeper truth — let's refine them down to the core." Data handling: This skill operates within your agent's trust boundary. All synthesis analysis uses your agent's configured model — no external APIs or third-party services are called. If your agent uses a cloud-hosted LLM (Claude, GPT, etc.), data is processed by that service as part of normal agent operation. This skill does not write files to disk.

When to Use

Activate this skill when the user asks:

  • "What's the core across all of these?"
  • "Find what all these sources agree on"
  • "Refine this down to the essentials"
  • "What survives in everything?"
  • "Create a Golden Master"

What This Does

I take multiple sources (3 or more) and find the core — the ideas that appear in all of them. Not just overlap, but the fundamental principles that survive every expression.

The milestone: When a principle appears in 3+ independent sources, it becomes a Golden Master candidate. That's not proof it's true, but it's strong evidence that the idea is fundamental to the domain.


How It Works

The Refinement Process

  1. Gather everything — all principles from all sources
  2. Look for threads — what ideas appear across sources?
  3. Test for consistency — same idea, not just same words?
  4. Classify — invariant (N≥3), domain-specific (N=2), or noise (N=1)
  5. Identify candidates — which invariants could be Golden Masters?

What Counts as Invariant?

A principle is invariant when:

  • It appears in 3 or more independent sources
  • The meaning stays consistent across all
  • It would survive if you rewrote any source

Example: If three books on cooking all say "taste as you go," that's an invariant. It survives because it's true, not because they copied each other.


What You'll Get

The Refinement Output

Synthesizing 4 sources: a1b2c3d4, e5f6g7h8, i9j0k1l2, m3n4o5p6

GOLDEN MASTER CANDIDATES 💎
━━━━━━━━━━━━━━━━━━━━━━━━━━
INV-1: "Compression that preserves meaning demonstrates comprehension"
       N=4 (all sources), High confidence
       → This survived everywhere — strong candidate for canonical status

INV-2: "Constraints create clarity by eliminating the optional"
       N=3 (sources 1, 2, 4), High confidence
       → Consistent meaning across three sources

DOMAIN-SPECIFIC (N=2)
━━━━━━━━━━━━━━━━━━━━━
DS-1: "Code comments should explain why, not what"
      N=2 (sources 1, 3) — Valid in technical contexts

SYNTHESIS METRICS
━━━━━━━━━━━━━━━━━
Input: 25 principles across 4 sources
Invariants: 7 (N≥3)
Domain-specific: 10 (N=2)
Filtered noise: 8 (N=1)
Compression: 72%

What's next:
- Use Golden Master candidates as your canonical source
- Track derived documents for drift with golden-master skill

The N-Count System

Level What It Means
N=1 One source only — might be unique to that context
N=2 Two sources — validated but could be coincidence
N≥3 Three+ sources — this is the core!

Why 3? Two sources agreeing could be coincidence. Three independent sources expressing the same idea? That's signal.


What I Need From You

Required: 3 or more things to synthesize

  • Extractions from essence-distiller/pbe-extractor
  • Raw text sources (I'll extract first)
  • Comparison results from pattern-finder/principle-comparator

Minimum: 3 sources Sweet spot: 4-6 sources More is fine: But returns diminish after 7-8


What I Can't Do

  • Declare truth — Golden Masters are candidates, not verdicts
  • Work with less than 3 — Use pattern-finder for 2 sources
  • Mix incompatible domains — Cooking and coding won't synthesize well
  • Override your judgment — I find patterns, you decide what's true

Technical Details

Output Format

{
  "operation": "synthesize",
  "metadata": {
    "source_count": 4,
    "source_hashes": ["a1b2c3d4", "e5f6g7h8", "i9j0k1l2", "m3n4o5p6"],
    "timestamp": "2026-02-04T12:00:00Z"
  },
  "result": {
    "invariant_principles": [
      {
        "id": "INV-1",
        "statement": "Compression that preserves meaning demonstrates comprehension",
        "n_count": 4,
        "confidence": "high",
        "golden_master_candidate": true
      }
    ],
    "domain_specific": [...],
    "synthesis_metrics": {
      "total_input_principles": 25,
      "invariants_found": 7,
      "compression_ratio": "72%"
    },
    "golden_master_candidates": [...]
  },
  "next_steps": [
    "Use Golden Master candidates as canonical source",
    "Track with golden-master skill for drift detection"
  ]
}

When You'll See share_text

If I find Golden Master candidates, I'll include:

"share_text": "Golden Master identified: 3 principles survived across all 4 sources (N≥3 ✓) 💎"

This is the culmination of the whole process — genuinely exciting when it happens!

Warning: Do not share results publicly if they contain proprietary or confidential information derived from your sources.


Error Messages

Situation What I'll Say
Not enough sources "I need at least 3 sources for synthesis — use pattern-finder for 2."
Different topics "These sources seem to be about different things — try related content."
No invariants "No principles appeared in 3+ sources — these might be genuinely different perspectives."

Voice Differences from principle-synthesizer

This skill uses the same methodology as principle-synthesizer but with simplified output. Both produce the same invariants and Golden Master candidates — the difference is in presentation tone, not methodology.

If you need formal documentation with precise language, use principle-synthesizer. If you want a discovery-focused experience, use this skill.


Related Skills

  • essence-distiller: Extract principles first (warm tone)
  • pbe-extractor: Extract principles first (technical tone)
  • pattern-finder: Compare 2 sources before synthesizing
  • principle-comparator: Compare 2 sources (technical)
  • principle-synthesizer: Technical version of this skill (formal language)
  • golden-master: Track relationships after synthesis

Sensitive Data Warning

  • Synthesis outputs may be stored in your chat history or logs
  • Avoid synthesizing proprietary information if outputs might be shared
  • Review outputs before sharing to ensure no confidential information is exposed

Required Disclaimer

This skill identifies invariant patterns, not verified truth. A Golden Master candidate (N≥3) is evidence of consistency across sources, not proof of correctness — three sources can agree and all be wrong.

Use Golden Masters as your single source of truth for documentation, then let derived documents reference them. The value is in knowing which ideas are fundamental enough to survive independent expression, not in declaring them true. Use your own judgment to evaluate correctness.


Built by Obviously Not — Tools for thought, not conclusions.

Usage Guidance
This skill appears internally consistent and lightweight. Before using it, be mindful that: (1) it will process whatever source texts you give it using the agent's configured model — if that model is cloud-hosted, data will be sent to the provider, so avoid feeding highly sensitive or proprietary content unless your privacy policy allows it; (2) the skill expects structured extractions or raw sources and may rely on outputs from other skills — ensure those upstream skills don't broaden access to secrets; (3) Golden Master candidates are heuristic (N≥3) — verify and vet candidates before publishing or operationalizing them. If you need stricter data residency, run the agent with an on-premise model or scrub/redact sensitive fields before submitting sources.
Capability Analysis
Type: OpenClaw Skill Name: core-refinery Version: 1.0.5 The 'Core Refinery' skill bundle consists of metadata and markdown instructions (SKILL.md) designed to guide an AI agent in synthesizing multiple text sources to identify recurring themes. It contains no executable code, external network calls, or file system operations, and its instructions are strictly aligned with its stated purpose of knowledge management and summarization.
Capability Assessment
Purpose & Capability
Name/description (finding invariants across multiple sources) match the SKILL.md instructions. The skill expects 3+ sources and/or extractions from related skills (essence-distiller, pattern-finder) which is reasonable for this use case.
Instruction Scope
The SKILL.md confines processing to the agent's configured model and explicitly says it does not write files. It asks for raw texts or extractions and describes a clear N-count synthesis process. Note: it will process whatever sources you provide (including confidential content) via whatever model the agent is configured to use; if that model is cloud-hosted, your data will be sent to the model provider as part of normal operation.
Install Mechanism
Instruction-only skill with no install spec and no code files. No artifacts are downloaded or written to disk by the skill itself.
Credentials
Requires no environment variables, credentials, or config paths. Declared inputs (3+ sources or extractions) are proportional to the stated task.
Persistence & Privilege
always:false and user-invocable:true. The skill does not request persistent presence or system-wide configuration changes.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install core-refinery
  3. After installation, invoke the skill by name or use /core-refinery
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.5
No file or documentation changes detected in this release. - Version bump to 1.0.5 with no additional modifications. - No updates to functionality, features, or documentation.
v1.0.4
- Added version number to the manifest and updated the homepage URL to point to the GitHub repository. - Revised data handling details: clarified that no external APIs or third-party services are called, and that data is processed by your agent’s configured model. - Removed “disable-model-invocation: true” from the manifest to reflect updated invocation capabilities. - Updated tags for improved discoverability (added "synthesis", "consolidation", "merging", etc.). - Small clarifications in how the skill operates and how data is handled; no changes to synthesis logic or output format.
v1.0.3
SEC-1 through SEC-6: Safety statement fix, stealth-mode warning, model backend clarification, Sensitive Data Warning section, share_text warnings
v1.0.2
Security improvements: added safety boundaries, disable-model-invocation, privacy notes, updated homepages
v1.0.1
Migrated to public GitHub repo, updated homepage URLs
v1.0.0
Initial release of Core Refinery — discover core ideas that persist across multiple sources. - Synthesizes 3 or more sources to identify invariant principles and Golden Master candidates (N≥3). - Classifies principles as invariant (N≥3), domain-specific (N=2), or unique/noise (N=1). - Provides structured outputs with synthesis metrics and next steps. - Friendly, discovery-focused tone with guidance for error situations and use-cases. - Technical JSON output and clear explanation of process included. - Designed for cross-domain synthesis; requires related sources for best results.
Metadata
Slug core-refinery
Version 1.0.5
License MIT-0
All-time Installs 3
Active Installs 3
Total Versions 6
Frequently Asked Questions

What is Core Refinery?

Find the core that runs through everything — the ideas that survive across all your sources. It is an AI Agent Skill for Claude Code / OpenClaw, with 1665 downloads so far.

How do I install Core Refinery?

Run "/install core-refinery" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Core Refinery free?

Yes, Core Refinery is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Core Refinery support?

Core Refinery is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Core Refinery?

It is built and maintained by Lee Brown (@leegitw); the current version is v1.0.5.

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