Laporan audit skill
neo4j-agent-memory-skill Laporan audit.
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.
Trust Score OpenAgentSkill
Trust Score OpenAgentSkill
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
Adopsi GitHub
Info62
101 star GitHub
Aktivitas star/fork
Peringatan57
101 star dan 35 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus88
2 bulan sejak push
Kejelasan lisensi
Lulus86
MIT
Kelengkapan README/SKILL.md
Lulus86
Metadata memuat konteks penggunaan dan alur kerja yang cukup
Risiko dependensi/runtime
Gagal28
command execution surface, credential or environment access
Ketersediaan pemasangan
Lulus92
npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill
Keamanan perintah pemasangan
Lulus92
Jalur pemasangan paket atau runtime standar
Cakupan izin
Gagal18
secrets or environment access, shell or command execution
Bukti repositori
Lulus86
https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill
Status peninjauan
Info66
Data tinjauan AI tersedia
Hasil terbukti Agent
Info54
Belum ada data hasil Agent
Pemeriksaan
Tinjauan pemasangan dan adopsi
Jalur pemasangan
92
npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill
Repositori
88
https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill
Lisensi
86
MIT
Pemeliharaan
88
2 bulan sejak push
Tinjauan AI
55
The SKILL.md excerpt is truncated in the review, but the visible content indicates a comprehensive reference with explicit warnings about version verification and authoritative sources.
Kelengkapan README/SKILL.md
86
Usable description available
Risiko dependensi
28
command execution surface, credential or environment access
Keamanan perintah pemasangan
92
Jalur pemasangan paket atau runtime standar
Cakupan izin
18
secrets or environment access, shell or command execution
Aktivitas star/fork
57
101 star dan 35 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Adopsi
68
101 star GitHub
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Peringatan
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Financial research output is not financial advice; require human review before any live investment decision
- The SKILL.md excerpt is truncated in the review, but the visible content indicates a comprehensive reference with explicit warnings about version verification and authoritative sources.
- Potential license mismatch: the repository is MIT but the referenced package is Apache-2.0; this is not a conflict for the skill itself but should be clarified in the skill documentation.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- Stars/forks activity: 101 stars, 35 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Metode
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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