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 neo4j-contrib/neo4j-skills --skill neo4j-document-import-skillgit clone --depth 1 https://github.com/neo4j-contrib/neo4j-skillsWrote 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/neo4j-contrib/neo4j-skills/neo4j-document-import-skill)<a href="https://agentmods.dev/skills/neo4j-contrib/neo4j-skills/neo4j-document-import-skill"><img src="https://agentmods.dev/badge/skills/neo4j-contrib/neo4j-skills/neo4j-document-import-skill/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/neo4j-contrib/neo4j-skills/neo4j-document-import-skill"><img src="https://agentmods.dev/badge/skills/neo4j-contrib/neo4j-skills/neo4j-document-import-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 311 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00187 | $0.05608 |
| Opus 5 | $0.00093 | $0.02804 |
| Sonnet 5 | $0.00037 | $0.01122 |
| Haiku 4.5 | $0.00019 | $0.00561 |
Grade A, and why
neo4j-document-import-skill 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 13d 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 — 586 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neo4j Document Import Skill
When to Use
- Ingesting PDFs, HTML, plain text, Markdown into Neo4j as a knowledge graph
- Chunking documents and storing
:Chunknodes with embeddings - Extracting entities and relationships from text with an LLM
- Using
SimpleKGPipeline(neo4j-graphrag) programmatically - Using Neo4j LLM Graph Builder (no-code web UI)
- Loading semi-structured JSON via
apoc.load.json - Connecting LangChain or LlamaIndex document loaders to Neo4j
When NOT to Use
- Structured CSV / relational data →
neo4j-import-skill - GraphRAG retrieval after ingestion →
neo4j-graphrag-skill - Vector index creation →
neo4j-vector-search-skill - Cypher query writing →
neo4j-cypher-skill
Approach Decision Table
| Situation | Approach |
|---|---|
| No code; drag-and-drop UX wanted | LLM Graph Builder web UI |
| Programmatic pipeline; PDFs/text | SimpleKGPipeline (neo4j-graphrag) |
| JSON / REST API responses | apoc.load.json or Python + UNWIND |
| LangChain already in stack | Neo4jGraph + document loader |
| LlamaIndex already in stack | Neo4jQueryEngine / Neo4jVectorStore |
| Chunk-only (no entity extraction) | Manual chunking + MERGE pattern |
Install
pip install neo4j-graphrag # includes SimpleKGPipeline
pip install neo4j-graphrag[openai] # + OpenAI LLM/embedder
pip install neo4j-graphrag[anthropic] # + Anthropic Claude
pip install neo4j-graphrag[google] # + Vertex AI / Gemini
pip install neo4j-graphrag[bedrock] # + Amazon Bedrock (boto3) — added v1.15.0
pip install neo4j-graphrag[ollama] # + Ollama (local)
pip install neo4j-graphrag[mistralai] # + MistralAI
pip install neo4j-graphrag[fuzzy-matching] # + FuzzyMatchResolver (rapidfuzz)
# spaCy entity resolver (Python <= 3.13 only — unsupported on 3.14+):
pip install neo4j-graphrag[nlp]
Requires: neo4j>=5.17.0 (driver 6.x supported), Python>=3.10, Neo4j>=5.18.1 (Aura>=5.18.0).
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.
- 13d ago First seen · 586 lines · 187 tokens per session scan A 5bdbc635e8a4
neo4j-document-import-skill is a skill published in the GitHub repository neo4j-contrib/neo4j-skills (109 stars, last pushed 5d ago), licensed MIT. It adds 187 tokens to every session and 5,608 once invoked, about $0.0009 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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