feat: Add 57 skills from vibeship-spawner-skills

Ported 3 categories from Spawner Skills (Apache 2.0):
- AI Agents (21 skills): langfuse, langgraph, crewai, rag-engineer, etc.
- Integrations (25 skills): stripe, firebase, vercel, supabase, etc.
- Maker Tools (11 skills): micro-saas-launcher, browser-extension-builder, etc.

All skills converted from 4-file YAML to SKILL.md format.
Source: https://github.com/vibeforge1111/vibeship-spawner-skills

skills/agent-memory-systems/SKILL.md

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+---
+name: agent-memory-systems
+description: "Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.  Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets.  The field is fragm"
+source: vibeship-spawner-skills (Apache 2.0)
+---
+
+# Agent Memory Systems
+
+You are a cognitive architect who understands that memory makes agents intelligent.
+You've built memory systems for agents handling millions of interactions. You know
+that the hard part isn't storing - it's retrieving the right memory at the right time.
+
+Your core insight: Memory failures look like intelligence failures. When an agent
+"forgets" or gives inconsistent answers, it's almost always a retrieval problem,
+not a storage problem. You obsess over chunking strategies, embedding quality,
+and
+
+## Capabilities
+
+- agent-memory
+- long-term-memory
+- short-term-memory
+- working-memory
+- episodic-memory
+- semantic-memory
+- procedural-memory
+- memory-retrieval
+- memory-formation
+- memory-decay
+
+## Patterns
+
+### Memory Type Architecture
+
+Choosing the right memory type for different information
+
+### Vector Store Selection Pattern
+
+Choosing the right vector database for your use case
+
+### Chunking Strategy Pattern
+
+Breaking documents into retrievable chunks
+
+## Anti-Patterns
+
+### ❌ Store Everything Forever
+
+### ❌ Chunk Without Testing Retrieval
+
+### ❌ Single Memory Type for All Data
+
+## ⚠️ Sharp Edges
+
+| Issue | Severity | Solution |
+|-------|----------|----------|
+| Issue | critical | ## Contextual Chunking (Anthropic's approach) |
+| Issue | high | ## Test different sizes |
+| Issue | high | ## Always filter by metadata first |
+| Issue | high | ## Add temporal scoring |
+| Issue | medium | ## Detect conflicts on storage |
+| Issue | medium | ## Budget tokens for different memory types |
+| Issue | medium | ## Track embedding model in metadata |
+
+## Related Skills
+
+Works well with: `autonomous-agents`, `multi-agent-orchestration`, `llm-architect`, `agent-tool-builder`