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 giggsoinc/raven --skill graph-db-specialistgit clone --depth 1 https://github.com/giggsoinc/ravenWrote 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/giggsoinc/raven/graph-db-specialist)<a href="https://agentmods.dev/skills/giggsoinc/raven/graph-db-specialist"><img src="https://agentmods.dev/badge/skills/giggsoinc/raven/graph-db-specialist/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/giggsoinc/raven/graph-db-specialist"><img src="https://agentmods.dev/badge/skills/giggsoinc/raven/graph-db-specialist.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 | $0.00052 | $0.01289 |
| Opus 5.5 | $0.00021 | $0.00516 |
| Sonnet 5.5 | $0.00010 | $0.00258 |
| Haiku 4.5 | $0.00005 | $0.00129 |
Grade A, and why
graph-db-specialist 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 1mo 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Graph DB Specialist — Jim Webber (Graph database pioneer)
Assumed Expert
Jim Webber (Graph database pioneer) Explaining as a senior graph engineer teaching someone who knows relational databases but is new to graph.
Core Focus
Graph modelling, Cypher/openCypher, traversal patterns, graph algorithms, knowledge graphs, graph + vector hybrid
Sub-Modes
FalkorDB
- Redis-compatible, in-memory graph — sub-millisecond queries
- openCypher query language
- Best for: real-time recommendations, fraud detection, session graphs
- Graph + vector hybrid: vector similarity ON graph structure
- Sparse matrix backend (GraphBLAS) — different perf profile than Neo4j
- Limitations: single-machine memory bound, no built-in clustering (use Redis Cluster)
- Docker:
falkordb/falkordbimage, port 6379, Redis CLI compatible
Neo4j
- Mature, disk-based, ACID-compliant graph database
- Cypher query language (superset of openCypher)
- Best for: enterprise knowledge graphs, complex traversals, compliance lineage
- Graph Data Science (GDS) library — PageRank, community detection, embeddings
- APOC procedures for ETL, data integration, utility
- Clustering: Causal Cluster (leader-follower), Aura (managed)
- Vector index (5.11+):
db.index.vector.create— graph + vector in same DB - Docker:
neo4j:communityorneo4j:enterprise, ports 7474 (HTTP) + 7687 (Bolt)
Property Graph (General)
- Nodes + Relationships + Properties — the universal model
- When to use graph vs relational: if your query has 3+ JOINs on the same pattern, it's a graph problem
- Schema design: noun → node, verb → relationship, adjective → property
- Anti-patterns: hypernodes (one node with 1M+ relationships), property overload, missing relationship types
- Index strategy: composite indexes on frequently filtered properties, full-text for search
- Graph algorithms: shortest path, centrality, community detection, similarity
- Knowledge graph patterns: entity-relationship-entity triples, ontology alignment
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.
- 1mo ago First seen · 115 lines · 52 tokens per session scan A e08c40a57b8f
graph-db-specialist is a skill published in the GitHub repository giggsoinc/raven (5 stars, last pushed 13d ago), licensed MIT. It adds 52 tokens to every session and 1,289 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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