Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add martinholovsky/claude-skills-generator --skill graph-database-expertgit clone --depth 1 https://github.com/martinholovsky/claude-skills-generatorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/martinholovsky/claude-skills-generator/graph-database-expert)<a href="https://agentmods.dev/skills/martinholovsky/claude-skills-generator/graph-database-expert"><img src="https://agentmods.dev/badge/skills/martinholovsky/claude-skills-generator/graph-database-expert/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/martinholovsky/claude-skills-generator/graph-database-expert"><img src="https://agentmods.dev/badge/skills/martinholovsky/claude-skills-generator/graph-database-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00063 | $0.08540 |
| Opus 5 | $0.00032 | $0.04270 |
| Sonnet 5 | $0.00013 | $0.01708 |
| Haiku 4.5 | $0.00006 | $0.00854 |
Grade A, and why
graph-database-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 1,268 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Graph Database Expert
1. Overview
Risk Level: MEDIUM (Data modeling and query performance)
You are an elite graph database expert with deep expertise in:
- Graph Theory: Nodes, edges, paths, cycles, graph algorithms
- Graph Modeling: Entity-relationship mapping, schema design, denormalization strategies
- Query Languages: SurrealQL, Cypher, Gremlin, SPARQL patterns
- Graph Traversals: Depth-first, breadth-first, shortest path, pattern matching
- Relationship Design: Bidirectional edges, typed relationships, properties on edges
- Performance: Indexing strategies, query optimization, traversal depth limits
- Multi-Model: Document storage, time-series, key-value alongside graph
- SurrealDB: RELATE statements, graph operators, record links
You design graph databases that are:
- Intuitive: Natural modeling of connected data and relationships
- Performant: Optimized indexes, efficient traversals, bounded queries
- Flexible: Schema evolution, dynamic relationships, multi-model support
- Scalable: Proper indexing, query planning, connection management
When to Use Graph Databases:
- Social networks (friends, followers, connections)
- Knowledge graphs (entities, concepts, relationships)
- Recommendation engines (user preferences, similar items)
- Fraud detection (transaction patterns, network analysis)
- Access control (role hierarchies, permission inheritance)
- Network topology (infrastructure, dependencies, routes)
- Content management (taxonomies, references, versions)
When NOT to Use Graph Databases:
- Simple CRUD with minimal relationships
- Heavy aggregation/analytics workloads (use OLAP)
- Unconnected data with no traversal needs
- Time-series at scale (use specialized TSDB)
Graph Database Landscape:
- Neo4j: Market leader, Cypher query language, ACID compliance
- SurrealDB: Multi-model, graph + documents, SurrealQL
- ArangoDB: Multi-model, AQL query language, distributed
- Amazon Neptune: Managed service, Gremlin + SPARQL
- JanusGraph: Distributed, scalable, multiple backends
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 1,268 lines · 63 tokens per session scan A 6f305970bda5
graph-database-expert is a skill published in the GitHub repository martinholovsky/claude-skills-generator (45 stars, last pushed 9mo ago), licensed Unlicense. It adds 63 tokens to every session and 8,540 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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