neo4j-agent-memory-skill
Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.
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High
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tessl review fix ./neo4j-agent-memory-skill/SKILL.mdSecurity
1 high severity finding. You should review these findings carefully before considering using this skill.
W007: Insecure credential handling detected in skill instructions.
What this means
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
Why it was flagged
The skill contains command and config examples that embed passwords and bearer/API keys directly (e.g., --password <pw>, --header "Authorization: Bearer <nams_api_key>", OPENAI_API_KEY "sk-..."), which would encourage or require an LLM to insert secret values verbatim when reproducing or filling in those examples.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required runtime workflow exposes an MCP tool surface (hosted at https://memory.neo4jlabs.com/mcp and REST at https://memory.neo4jlabs.com/v1/) that accepts user-contributed free-text like conversation content and allows readouts via tools such as memory_store_message / memory_get_context, so outsiders can submit poison into the service for the agent to later retrieve and process.
- Repository
- neo4j-contrib/neo4j-skills
- Commit
a9a5e78
- Audited
- Security analysis
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