{"slug":"neo4j-contrib-neo4j-agent-memory-skill","name":"neo4j-agent-memory-skill","description":"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.","long_description":"---\nname: neo4j-agent-memory-skill\ndescription: 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.\nversion: 1.0.6\n---\n\n# neo4j-agent-memory\n\nAuthoritative reference for the `neo4j-agent-memory` Python package — a Neo4j Labs project that gives AI agents three distinct memory layers (short-term, long-term, reasoning) in a single knowledge graph.\n\n> ⚠️ **Verify authoritative state before writing.** Version numbers, extras, tool counts, and API surface change between releases. The values in this skill reflect a specific point in time. Before publishing anything version-sensitive, confirm against **PyPI** (`https://pypi.org/project/neo4j-agent-memory/`) and the **GitHub README** (`https://github.com/neo4j-labs/agent-memory`). PyPI is the authoritative source for version numbers — never infer.\n\n## When to Use\n\n- Building AI agents that need persistent memory (short-term, long-term, reasoning traces) backed by Neo4j\n- Using the `neo4j-agent-memory` Python package or the hosted NAMS service at memory.neo4jlabs.com\n- Integrating agent memory with LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, OpenAI Agents, LlamaIndex, or Microsoft Agent Framework\n- Writing documentation, tutorials, or positioning content about graph-native agent memory\n- Comparing graph-native memory against vector-only approaches\n\n## When NOT to Use\n\n- **Plain Neo4j driver connections** (no memory layer needed) → use `neo4j-driver-python-skill`\n- **Writing or optimizing Cypher queries** → use `neo4j-cypher-skill`\n- **GraphRAG retrieval pipelines** → use `neo4j-graphrag-skill`\n\n---\n\n## Project at a Glance\n\n| Field | Value |\n|-------|-------|\n| Package | `neo4j-agent-memory` |\n| PyPI | https://pypi.org/project/neo4j-agent-memory/ |\n| GitHub | https://github.com/neo4j-labs/agent-memory |\n| Canonical docs | https://neo4j.com/labs/agent-memory/ |\n| Hosted service | https://memory.neo4jlabs.com (NAMS — early-access, not yet documented on official project pages) |\n| Hosted MCP endpoint | https://memory.neo4jlabs.com/mcp (SSE, bearer auth) |\n| License | Apache-2.0 |\n| Python | 3.10+ |\n| Neo4j | 5.20+ (required for vector indexes) |\n| Status | Experimental (Neo4j Labs, community-supported) |\n| Current version (at time of writing) | **0.1.1** — **always verify PyPI before citing** |\n\n## What It Is (One Sentence)\n\nA graph-native memory system for AI agents that stores conversations, builds knowledge graphs, and records agent reasoning — all as connected nodes in a single Neo4j database.\n\n## Consumption Models\n\n`neo4j-agent-memory` ships in two consumption models. They are the same underlying project — the differences are how you run it, how you authenticate, and what's managed for you.\n\n| Option | What It Is | When to Choose |\n|--------|------------|----------------|\n| **Self-hosted library** | `pip install neo4j-agent-memory` + your own Neo4j (local / Docker / Aura). Full Python API, local MCP server, and framework integrations run in your process. | Dev, on-prem data, custom extraction pipelines, full control, bringing your own embeddings / LLMs. |\n| **Hosted (NAMS)** | Managed service at `https://memory.neo4jlabs.com`. Per-workspace isolated Neo4j Aura database, REST API, remote MCP endpoint, web console. | Zero-infra trials, sharing memory across agents / machines, demos, teams that don't want to run Neo4j. |\n\n> ⚠️ **NAMS is reachable but not yet referenced in the GitHub README or `neo4j.com/labs/agent-memory/`.** Treat it as early-access / soft-launched. Do not assert SLAs, pricing, or GA status in published content. See the **Hosted Service (NAMS)** section below for details.\n\n## The Three Memory Types\n\nThe defining architectural feature. Every piece of content describing the project should lead with this trinity.\n\n| Memory Type | Stores | Color Convention |\n|-------------|--------|------------------|\n| **Short-Term** | Conversation messages, session history, sequential message chains, metadata-filtered search, LLM-powered summaries | Green (`#B2F2BB` / `#2F9E44`) |\n| **Long-Term** | Entities (people, places, orgs), preferences, facts, and the relationships between them — built automatically from conversations via the POLE+O model | Orange/Yellow (`#FFEC99` / `#F08C00`) |\n| **Reasoning** | Decision traces, tool call provenance, thought-action-outcome chains — so the agent can learn from its own past reasoning patterns | Purple (`#D0BFFF` / `#9C36B5`) |\n\n**Reasoning memory is the primary competitive differentiator.** Most competing systems cover short-term and long-term but treat reasoning as an afterthought or omit it entirely. Lead with this when positioning.\n\n## The POLE+O Model\n\nLong-term memory uses the POLE+O entity framework — the canonical entity classification for this project:\n\n- **P**erson\n- **O**rganization\n- **L**ocation\n- **E**vent\n- **+O** Object (anything that doesn't fit the core four — products, concepts, projects, etc.)\n\nWhen diagramming the data model, use ellipses for entity nodes and labeled arrows (UPPER_SNAKE_CASE) for relationships, consistent with Neo4j Browser conventions.\n\n## Installation\n\nCore install plus extras. The extras pattern is `pip install neo4j-agent-memory[<extra>]`.\n\n```bash\npip install neo4j-agent-memory                  # Core\npip install neo4j-agent-memory[openai]          # + OpenAI embeddings\npip install neo4j-agent-memory[mcp]             # + MCP server\npip install neo4j-agent-memory[langchain]       # + LangChain\npip install neo4j-agent-memory[all]             # Everything\n```\n\n**Full extras list** (subject to change — verify PyPI): `all`, `anthropic`, `aws`, `bedrock`, `cli`, `crewai`, `extraction`, `full`, `fuzzy`, `gliner`, `google`, `google-adk`, `langchain`, `llamaindex`, `mcp`, `microsoft-agent`, `observability`, `openai`, `openai-agents`, `opentelemetry`, `opik`, `pydantic-ai`, `sentence-transformers`, `spacy`, `strands`, `vertex-ai`.\n\n## Python API (Quickstart)\n\nCanonical import pattern and basic usage. This is the shape to reproduce in tutorials and examples.\n\n```python\nimport asyncio\nfrom neo4j_agent_memory import MemoryClient, MemorySettings\n\nasync def main():\n    settings = MemorySettings(\n        neo4j={\"uri\": \"bolt://localhost:7687\", \"password\": \"your-password\"}\n    )\n\n    async with MemoryClient(settings) as memory:\n        # Short-term: store a conversation message\n        await memory.short_term.add_message(\n            session_id=\"user-123\",\n            role=\"user\",\n            content=\"Hi, I'm John and I love Italian food!\"\n        )\n\n        # Long-term: build the knowledge graph\n        await memory.long_term.add_entity(\"John\", \"PERSON\")\n        await memory.long_term.add_preference(\n            category=\"food\",\n            preference=\"Loves Italian cuisine\"\n        )\n\n        # Get combined context for an LLM prompt\n        context = await memory.get_context(\n            \"What restaurant should I recommend?\",\n            session_id=\"user-123\"\n        )\n        print(context)\n\nasyncio.run(main())\n```\n\n**Note the async context manager pattern** (`async with MemoryClient(settings) as memory:`) — this is the canonical form.\n\n## MCP Server\n\nExposes memory as tools for MCP-compatible AI assistants (Claude Desktop, Claude Code, Cursor, VS Code Copilot).\n\n### Invocation\n\nThe authoritative one-liner (no install needed):\n\n```bash\nuvx \"neo4j-agent-memory[mcp]\" mcp serve --password <neo4j-password>\n```\n\nInstall-local alternative:\n\n```bash\nneo4j-agent-memory mcp serve --password <pw>\n```\n\n### Transports and Profiles\n\n```bash\n# stdio (default — Claude Desktop, Claude Code)\nneo4j-agent-memory mcp serve --password <pw>\n\n# SSE (network deployment)\nneo4j-agent-memory mcp serve --transport sse --port 8080 --password <pw>\n\n# Core profile — fewer tools, less context overhead\nneo4j-agent-memory mcp serve --profile core --password <pw>\n\n# Session continuity across conversations\nneo4j-agent-memory mcp serve \\\n  --session-strategy per_day \\\n  --user-id alice \\\n  --password <pw>\n```\n\n### Tool Profiles\n\n| Profile | Tools | Contents |\n|---------|-------|----------|\n| **core** | 6 | `memory_search`, `memory_get_context`, `memory_store_message`, `memory_add_entity`, `memory_add_preference`, `memory_add_fact` |\n| **extended** (default) | 16 | Core + conversation history, entity details, graph export, relationship creation, reasoning traces, observations, read-only Cypher |\n\nAs of v0.1.1, `memory_add_fact` accepts a `metadata` parameter, bringing it to parity with `memory_add_entity`.\n\n### Claude Code Registration\n\n```bash\nclaude mcp add neo4j-agent-memory -- \\\n  uvx \"neo4j-agent-memory[mcp]\" mcp serve --password <neo4j-password>\n```\n\n### Claude Desktop Config\n\n```json\n{\n  \"mcpServers\": {\n    \"neo4j-agent-memory\": {\n      \"command\": \"uvx\",\n      \"args\": [\"neo4j-agent-memory[mcp]\", \"mcp\", \"serve\", \"--password\", \"your-password\"],\n      \"env\": {\n        \"OPENAI_API_KEY\": \"sk-...\"\n      }\n    }\n  }\n}\n```\n\n> For the **hosted** MCP endpoint at `memory.neo4jlabs.com/mcp`, see the **Hosted Service (NAMS)** section below — it uses SSE transport and bearer-token auth, not a local `uvx` invocation.\n\n## Hosted Service (NAMS)\n\n**NAMS** — Neo4j Agent Memory Service — is the managed deployment of `neo4j-agent-memory` at `https://memory.neo4jlabs.com`. It bundles the REST API, the MCP server, a web console, and per-workspace Neo4j Aura databases.\n\n> ⚠️ **Verify against the live service before citing.** NAMS is not documented on the GitHub README or `neo4j.com/labs/agent-memory/`. Endpoint shapes, tool counts, auth flows, and limits can change without a release note. Before publishing anything NAMS-specific, re-check the live site and the OpenAPI spec at `/openapi.json`.\n\n### Surface\n\n- **Base URL:** `https://memory.neo4jlabs.com`\n- **Web console:** root URL — workspace management, memory browsing, entity visualization\n- **REST API:** `https://memory.neo4jlabs.com/v1/` — OpenAPI spec at `/openapi.json`; covers conversations, entities, observations, reasoning traces, and read-only Cypher\n- **MCP endpoint:** `https://memory.neo4jlabs.com/mcp` — SSE transport, exposes the hosted tool set, bearer-token auth\n\n### Auth\n\n- **API keys**, prefixed `nams_`, created and rotated from the web console — used as a bearer token for REST and MCP\n- **Auth0 OAuth2 (PKCE)** + scoped JWTs for interactive user flows\n\nDon't mix these with the self-hosted library's `--password` Neo4j credential — they serve different sides of the stack.\n\n### Storage Model\n\nEach workspace is backed by an **isolated Neo4j Aura database**, provisioned on demand. Bring-your-own-Neo4j is supported as an alternative, configured per workspace.\n\n### Rate Limits\n\nUsage counters are tracked per API key / workspace. Exact limits are not publicly documented — check the console or re-verify against the service before committing customers to numbers.\n\n### Claude Code Registration (Hosted MCP)\n\n```bash\nclaude mcp add --transport sse neo4j-agent-memory-hosted \\\n  https://memory.neo4jlabs.com/mcp \\\n  --header \"Authorization: Bearer <nams_api_key>\"\n```\n\n### Claude Desktop Config (Hosted MCP)\n\n```json\n{\n  \"mcpServers\": {\n    \"neo4j-agent-memory-hosted\": {\n      \"url\": ","tagline":"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. 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Creators can claim the listing to update ownership signals."},"stats":{"stars":101,"forks":35,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":36.86},"quality":{"score":66,"tier":"promising","label":"Promising","summary":"Useful candidate, but compare it with alternatives before adopting.","signals":[{"label":"GitHub stars","value":"101","tone":"neutral"},{"label":"Freshness","value":"16d ago","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"MIT","tone":"neutral"}],"warnings":["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."]},"trust":{"version":"trust-score-v5","score":56,"base_score":64,"outcome_confidence":0,"tier":"risk","label":"Do not auto-install","summary":"Trust Score v5 found insufficient evidence for agent installation. 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Treat this as discovery material, not an executable recommendation.","recommendedAction":"Choose a stronger alternative or inspect the source manually before any install attempt.","decision":{"install_policy":"human_review_before_install","auto_install_allowed":false,"human_review_required":true,"sandbox_first":true,"agent_action":"Compare alternatives before installing.","reasoning":["56/100 Trust Score v5","64/100 Trust Score v4 baseline","Needs more real agent outcomes before unattended install","Install path is available","Review before production"],"review_required_when":["The workspace contains production secrets, payments, private customer data, or irreversible actions.","The install command requests shell, network, credential, database, or broad filesystem access.","Outcome evidence is missing, recently failed, or required human review.","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"]},"dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":62,"weight":0.13,"status":"info","detail":"101 GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":57,"weight":0.08,"status":"warn","detail":"101 stars, 35 forks; 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issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"16d since push"},{"status":"pass","label":"License clarity","detail":"MIT"},{"status":"pass","label":"README/SKILL.md completeness","detail":"Metadata includes enough usage and workflow context"},{"status":"fail","label":"Dependency/runtime risk","detail":"command execution surface, credential or environment access"},{"status":"pass","label":"Install availability","detail":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"fail","label":"Permission surface","detail":"secrets or environment access, shell or command execution"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill"},{"status":"info","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"info","label":"OpenAgentSkill usage","detail":"No local usage activity yet"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Install command has no obvious high-risk pattern","Outcome loop is ready but needs first real agent run"],"warnings":["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.","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","No real agent outcome reports yet","Human review required before unattended installation"],"evidence":{"stars":"101 GitHub stars","repoActivity":"101 stars, 35 forks","lastPushed":"16d since push","license":"MIT","repository":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill","install":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, shell or command execution","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet","agentProvenScore":0,"outcomeConfidence":"0%","installPolicy":"human_review_before_install"},"installReadiness":{"ready":true,"command":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","policy":"human_review_before_install","label":"Human review before install","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","16d since push","Financial domain: human review is required before use in a live investment workflow.","Trust Score v5 requires review or sandbox-only use before install."]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"medium","label":"Review before production","notes":["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.","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"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Compare alternatives before installing."},"outcome_loop":{"version":"openagentskill-agent-outcome-v4","required_after_install":true,"endpoint":"/api/agent/outcome","method":"POST","event_id_source":"feedback.event_id, install_receipt.resolve_event_id, or decision_packet.outcome_feedback.event_id","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"required_fields":["event_id","skill_slug","task"],"quality_fields":["task_success","output_quality","error_type","human_review_required","used_in_production","workspace","evidence_url","time_to_useful_ms","source_version"],"ranking_inputs_updated":["Trust Score v5 outcome confidence","Agent Proven Score","Resolve ranking task-fit evidence","Skill detail machine-readable metadata","Outcome leaderboard"]},"agent_contract":{"suited_tasks":["design-creative","agent-skill"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"install_command":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","trust_score":56,"trust_version":"trust-score-v5","risk_level":"medium","do_not_use_when":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Autonomous investment, trading, tax, or suitability decisions without a qualified human review"],"before_install":["Read the audit page and machine-readable metadata.","Confirm the install command, license, and permission surface fit the workspace.","Get explicit human approval or choose an alternative before installing."],"after_run":["Report the outcome to /api/agent/outcome using the resolve event id.","Include output_quality, workspace, human_review_required, and evidence_url when available.","Re-resolve before broad production rollout."]},"bestFor":["design-creative","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Autonomous investment, trading, tax, or suitability decisions without a qualified human review"],"knownRisks":["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.","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"],"backward_compatible":{"trust_score_v4":{"version":"trust-score-v4","score":64,"tier":"review","label":"Manual review","summary":"Potentially useful, but at least one trust signal needs human inspection."}}},"trust_score_v4":{"version":"trust-score-v4","score":64,"tier":"review","label":"Manual review","summary":"Potentially useful, but at least one trust signal needs human inspection.","recommendedAction":"Inspect the repository, license, and recent activity before connecting it to agent workflows.","dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":62,"weight":0.13,"status":"info","detail":"101 GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":57,"weight":0.08,"status":"warn","detail":"101 stars, 35 forks; issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"16d since push"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"MIT"},{"id":"documentation","label":"README/SKILL.md completeness","score":86,"weight":0.14,"status":"pass","detail":"Metadata includes enough usage and workflow context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":28,"weight":0.12,"status":"fail","detail":"command execution surface, credential or environment access"},{"id":"installability","label":"Install availability","score":92,"weight":0.1,"status":"pass","detail":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill"},{"id":"install_safety","label":"Install command safety","score":92,"weight":0.1,"status":"pass","detail":"standard package or runtime install path"},{"id":"permission_surface","label":"Permission surface","score":18,"weight":0.07,"status":"fail","detail":"secrets or environment access, shell or command execution"},{"id":"repository","label":"Repository evidence","score":86,"weight":0.04,"status":"pass","detail":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill"},{"id":"review_status","label":"Review status","score":66,"weight":0.05,"status":"info","detail":"AI review data available"},{"id":"agent_outcomes","label":"Agent Proven outcomes","score":54,"weight":0.13,"status":"info","detail":"No agent outcome data yet"}],"checks":[{"status":"info","label":"GitHub adoption","detail":"101 GitHub stars"},{"status":"warn","label":"Stars/forks activity","detail":"101 stars, 35 forks; issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"16d since push"},{"status":"pass","label":"License clarity","detail":"MIT"},{"status":"pass","label":"README/SKILL.md completeness","detail":"Metadata includes enough usage and workflow context"},{"status":"fail","label":"Dependency/runtime risk","detail":"command execution surface, credential or environment access"},{"status":"pass","label":"Install availability","detail":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"fail","label":"Permission surface","detail":"secrets or environment access, shell or command execution"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill"},{"status":"info","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"info","label":"OpenAgentSkill usage","detail":"No local usage activity yet"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Install command has no obvious high-risk pattern"],"warnings":["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.","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"],"evidence":{"stars":"101 GitHub stars","repoActivity":"101 stars, 35 forks","lastPushed":"16d since push","license":"MIT","repository":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill","install":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, shell or command execution","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"installReadiness":{"ready":true,"command":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","policy":"human_review_before_install","label":"Human review before install","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","16d since push","Financial domain: human review is required before use in a live investment workflow."]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"medium","label":"Review before production","notes":["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.","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"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Human review or sandbox validation is required before automatic installation."},"bestFor":["design-creative","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Autonomous investment, trading, tax, or suitability decisions without a qualified human review"],"knownRisks":["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.","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"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":25,"level":"avoid_auto_install","label":"Avoid automatic install","safety_tier":{"tier":"blocked","label":"Blocked for auto-install","badge":"BLOCKED","summary":"This skill should not be selected by an agent without explicit human security review.","recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","auto_install_policy":"block","reasons":["Metadata combines secrets access with shell or command execution","High-risk permission hints: Shell or command execution, Secrets or environment access"]},"auto_install_allowed":false,"human_review_required":true,"blocked":true,"audit_risk":"needs_review","permission_hints":[{"id":"shell","label":"Shell or command execution","reason":"Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.","severity":"high"},{"id":"browser","label":"Browser automation","reason":"Skill may drive a browser or interact with web pages.","severity":"medium"},{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"},{"id":"filesystem","label":"Filesystem access","reason":"Skill may read or write project files, documents, generated artifacts, or local workspace state.","severity":"medium"},{"id":"secrets","label":"Secrets or environment access","reason":"Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.","severity":"high"},{"id":"database","label":"Database access","reason":"Skill may inspect schemas, query databases, or work with persistent stores.","severity":"medium"}],"policy_warnings":["High-risk permission hints: Shell or command execution, Secrets or environment access","Dependency or permission surface needs review"],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"blocked","label":"Blocked for auto-install","badge":"BLOCKED","auto_install_policy":"block","auto_install_allowed":false,"blocked":true,"human_review_required":true,"recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","reasons":["Metadata combines secrets access with shell or command execution","High-risk permission hints: Shell or command execution, Secrets or environment access"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"failed","score":61,"risk_level":"high","decision":{"recommendation":"do_not_auto_install","reason":"Agent safety gate: This skill should not be selected by an agent without explicit human security review.","auto_install_allowed":false,"policy":"block","human_review_required":true},"blockers":["Agent safety gate: This skill should not be selected by an agent without explicit human security review.","Permission surface: secrets or environment access, shell or command execution"],"warnings":["Trust score: Potentially useful, but at least one trust signal needs human inspection.","Audit score: Needs review","High-risk permission hints: Shell or command execution, Secrets or environment access","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"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"pass","score":94,"required_for_auto_install":true,"detail":"Task wording matches this skill metadata.","evidence":["Evaluate neo4j-agent-memory-skill before installing it in an agent workflow","design-creative","RAG and knowledge workflows; Claude Code teams; builders willing to evaluate younger projects"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill"]},{"id":"trust_score","label":"Trust score","status":"warn","score":64,"required_for_auto_install":true,"detail":"Potentially useful, but at least one trust signal needs human inspection.","evidence":["Manual review","101 GitHub stars","MIT"]},{"id":"audit_score","label":"Audit score","status":"warn","score":73,"required_for_auto_install":true,"detail":"Needs review","evidence":["Dependency or permission surface needs review"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"fail","score":25,"required_for_auto_install":true,"detail":"This skill should not be selected by an agent without explicit human security review.","evidence":["Do not auto-install. Inspect the source, dependencies, and permission surface first.","Metadata combines secrets access with shell or command execution"]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"pass","score":86,"required_for_auto_install":false,"detail":"Metadata includes enough usage and workflow context","evidence":["Strong README/SKILL.md context"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"MIT","evidence":["MIT"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"16d since push","evidence":["16d since push"]},{"id":"permission_surface","label":"Permission surface","status":"fail","score":18,"required_for_auto_install":true,"detail":"secrets or environment access, shell or command execution","evidence":["Shell or command execution: high","Browser automation: medium","Network access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/neo4j-contrib-neo4j-agent-memory-skill/evals","api":"/api/agent/evals?slug=neo4j-contrib-neo4j-agent-memory-skill","text":"/api/agent/evals?slug=neo4j-contrib-neo4j-agent-memory-skill&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"neo4j-contrib-neo4j-agent-memory-skill","name":"neo4j-agent-memory-skill","description":"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.","category":"design-creative","url":"https://www.openagentskill.com/skills/neo4j-contrib-neo4j-agent-memory-skill","repository":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill","github_repo":"neo4j-contrib/neo4j-skills"},"suited_tasks":["RAG and knowledge workflows","Claude Code teams","builders willing to evaluate younger projects","Chunk documents","Create embeddings","Retrieve and cite relevant passages","Inspect repository metadata","Compare code changes"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","OpenAI Agents","LangChain","LlamaIndex","Browser agents"],"install":{"command":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add neo4j-contrib-neo4j-agent-memory-skill"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"neo4j-agent-memory-skill\" agent skill from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"neo4j-agent-memory-skill\" as a Claude Code skill from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"neo4j-agent-memory-skill\" from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/neo4j-contrib-neo4j-agent-memory-skill/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/neo4j-contrib-neo4j-agent-memory-skill"},"trust":{"score":64,"label":"Manual review","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"101 GitHub stars","repoActivity":"101 stars, 35 forks","lastPushed":"16d since push","license":"MIT","repository":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill","install":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, shell or command execution","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","agent-skill"],"known_risks":["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.","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"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":73,"risk_level":"needs_review","risk_label":"Needs review","warnings":["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"]},"safety_gate":{"tier":"blocked","label":"Blocked for auto-install","auto_install_policy":"block","auto_install_allowed":false,"human_review_required":true,"blocked":true,"recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first."},"quality":{"score":66,"label":"Promising"},"supply":{"track":"Design and creative production","scenario":"RAG and knowledge","maintenance":"16d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","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.","No OpenAgentSkill engagement data yet","High-risk permission hints: Shell or command execution, Secrets or environment access","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"],"agent_contract":{"task_input":"Use neo4j-agent-memory-skill in an agent workflow","recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","install_policy":"block","minimum_review_before_use":["Trust: 64/100 Manual review","Audit: 73/100 Needs review","Safety: 25/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"neo4j-contrib-neo4j-agent-memory-skill (neo4j-agent-memory-skill)","install_command":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","risk_summary":"Needs review; Blocked for auto-install; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"neo4j-contrib-neo4j-agent-memory-skill","task":"Use neo4j-agent-memory-skill in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/neo4j-contrib-neo4j-agent-memory-skill","api":"https://www.openagentskill.com/api/agent/skills/neo4j-contrib-neo4j-agent-memory-skill","audit":"https://www.openagentskill.com/skills/neo4j-contrib-neo4j-agent-memory-skill/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=neo4j-contrib-neo4j-agent-memory-skill&task=Use%20neo4j-agent-memory-skill%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20neo4j-agent-memory-skill%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20neo4j-agent-memory-skill%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/neo4j-contrib-neo4j-agent-memory-skill/install","manifest":"https://www.openagentskill.com/api/registry/manifest/neo4j-contrib-neo4j-agent-memory-skill"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"neo4j-contrib-neo4j-agent-memory-skill","name":"neo4j-agent-memory-skill","description":"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.","category":"design-creative","url":"https://www.openagentskill.com/skills/neo4j-contrib-neo4j-agent-memory-skill","repository":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill","github_repo":"neo4j-contrib/neo4j-skills"},"suited_tasks":["RAG and knowledge workflows","Claude Code teams","builders willing to evaluate younger projects","Chunk documents","Create embeddings","Retrieve and cite relevant passages","Inspect repository metadata","Compare code changes"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","OpenAI Agents","LangChain","LlamaIndex","Browser agents"],"install":{"command":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add neo4j-contrib-neo4j-agent-memory-skill"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"neo4j-agent-memory-skill\" agent skill from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"neo4j-agent-memory-skill\" as a Claude Code skill from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"neo4j-agent-memory-skill\" from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/neo4j-contrib-neo4j-agent-memory-skill/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/neo4j-contrib-neo4j-agent-memory-skill"},"trust":{"score":64,"label":"Manual review","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"101 GitHub stars","repoActivity":"101 stars, 35 forks","lastPushed":"16d since push","license":"MIT","repository":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill","install":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","installSafety":"standard package or runtime install path","permissionSurface":"secrets or environment access, shell or command execution","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","agent-skill"],"known_risks":["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.","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"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":73,"risk_level":"needs_review","risk_label":"Needs review","warnings":["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"]},"safety_gate":{"tier":"blocked","label":"Blocked for auto-install","auto_install_policy":"block","auto_install_allowed":false,"human_review_required":true,"blocked":true,"recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first."},"quality":{"score":66,"label":"Promising"},"supply":{"track":"Design and creative production","scenario":"RAG and knowledge","maintenance":"16d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","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.","No OpenAgentSkill engagement data yet","High-risk permission hints: Shell or command execution, Secrets or environment access","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"],"agent_contract":{"task_input":"Use neo4j-agent-memory-skill in an agent workflow","recommended_action":"Do not auto-install. Inspect the source, dependencies, and permission surface first.","install_policy":"block","minimum_review_before_use":["Trust: 64/100 Manual review","Audit: 73/100 Needs review","Safety: 25/100 Avoid automatic install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"neo4j-contrib-neo4j-agent-memory-skill (neo4j-agent-memory-skill)","install_command":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","risk_summary":"Needs review; Blocked for auto-install; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"neo4j-contrib-neo4j-agent-memory-skill","task":"Use neo4j-agent-memory-skill in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/neo4j-contrib-neo4j-agent-memory-skill","api":"https://www.openagentskill.com/api/agent/skills/neo4j-contrib-neo4j-agent-memory-skill","audit":"https://www.openagentskill.com/skills/neo4j-contrib-neo4j-agent-memory-skill/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=neo4j-contrib-neo4j-agent-memory-skill&task=Use%20neo4j-agent-memory-skill%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20neo4j-agent-memory-skill%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20neo4j-agent-memory-skill%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/neo4j-contrib-neo4j-agent-memory-skill/install","manifest":"https://www.openagentskill.com/api/registry/manifest/neo4j-contrib-neo4j-agent-memory-skill"}},"supply_profile":{"track":{"slug":"design","label":"Design and creative production","shortLabel":"Design","description":"Design assets, images, video, audio, multimodal media, presentation, and creative production skills."},"scenario":{"label":"RAG and knowledge","description":"I need my agent to build a RAG workflow over documents and retrieve reliable context.","useCases":[{"slug":"rag-knowledge","title":"RAG and knowledge"},{"slug":"github-automation","title":"GitHub automation"},{"slug":"local-desktop","title":"Local desktop"}]},"applicableAgents":["Claude Code","OpenAI Agents","Cursor","LangChain","LlamaIndex"],"install":{"ready":true,"command":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":101,"starsLabel":"101","forks":35,"license":"MIT","qualityScore":66,"trustScore":64,"auditScore":73},"maintenance":{"status":"fresh","label":"16d since push","daysSincePush":16,"lastPushedAt":"2026-08-19T19:45:51+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["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."]},"coverageTags":["Design","RAG and knowledge","design-creative","agent-skill"]},"audit":{"audit_score":73,"risk_level":"needs_review","risk_label":"Needs review","quality_score":66,"trust_score":64,"maintenance_score":100,"security_score":68,"install_score":92,"warnings":["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"]},"quality_signals":{"model":"v2","star_score":14.06,"usage_score":0,"review_score":4.8,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code","OpenAI Agents","Cursor","LangChain","LlamaIndex","Browser agents"],"use_cases":[{"slug":"rag-knowledge","title":"RAG and knowledge","url":"https://www.openagentskill.com/use-cases/rag-knowledge"},{"slug":"github-automation","title":"GitHub automation","url":"https://www.openagentskill.com/use-cases/github-automation"},{"slug":"local-desktop","title":"Local desktop","url":"https://www.openagentskill.com/use-cases/local-desktop"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"}],"stacks":[{"slug":"rag-knowledge-base","title":"RAG knowledge base","url":"https://www.openagentskill.com/collections/rag-knowledge-base"},{"slug":"web-data-pipeline","title":"Web data pipeline","url":"https://www.openagentskill.com/collections/web-data-pipeline"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"}],"install":"npx skills add neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add neo4j-contrib-neo4j-agent-memory-skill","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"neo4j-agent-memory-skill\" agent skill from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"neo4j-agent-memory-skill\" as a Claude Code skill from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"neo4j-agent-memory-skill\" from https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: 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. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"neo4j-contrib-neo4j-agent-memory-skill\",\"task\":\"Install neo4j-agent-memory-skill\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill","github_repo":"neo4j-contrib/neo4j-skills","version":"1.0.6","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/neo4j-contrib-neo4j-agent-memory-skill","repository":"https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill","api":"/api/agent/skills/neo4j-contrib-neo4j-agent-memory-skill","install_api":"/api/skills/neo4j-contrib-neo4j-agent-memory-skill/install"},"meta":{"created_at":"2026-08-19T20:35:33.665332+00:00","updated_at":"2026-09-01T11:59:28.941454+00:00","agent_friendly":true}}