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Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
基于 SOC 职业分类
正在显示 SKILL.md
| name | Core Refinery |
| description | Find the core that runs through everything — the ideas that survive across all your sources. |
| homepage | https://app.obviouslynot.ai/skills/core-refinery |
| user-invocable | true |
| emoji | 💎 |
| tags | ["core-ideas","refinement","multi-source","golden-master","knowledge-compression","invariant-patterns"] |
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."
Activate this skill when the user asks:
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.
A principle is invariant when:
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.
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
| 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.
Required: 3 or more things to synthesize
Minimum: 3 sources Sweet spot: 4-6 sources More is fine: But returns diminish after 7-8
{
"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
...
...
If I find Golden Master candidates, I'll include:
"share_text": "Golden Master identified: 3 principles survived across all 4 sources (N≥3 ✓) obviouslynot.ai/pbd/{hash} 💎"
This is the culmination of the whole process — genuinely exciting when it happens!
| 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." |
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.
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.