跳到正文
cccskills
免费在 GitHub 公开

agentdb-cypher

Execute Cypher queries against AgentDB's graph backend. Use when the user wants to write a custom traversal that the standard tools don't cover, or when explaining graph state.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(1)

  • SKILL.md1.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Cypher Query

Run arbitrary Cypher against the AgentDB graph backend. The native binding accepts standard openCypher; AgentDB also adds a few extensions (uplift, confidence properties on edges).

When to use

  • Need a query the standard agentdb_causal_* tools don't cover
  • Multi-hop traversal with custom filtering
  • Aggregation queries — count nodes by type, find hub nodes, etc.
  • Migration / inspection during debugging

API

agentdb_causal_query(
  cypher: <query string>,
  params?: { ... }
)

Returns: { rows, stats: { execMs, rowsMatched, rowsReturned } }

Example queries

-- Top 10 most-cited skills
MATCH (s:Skill)<-[r:references]-(:Episode)
RETURN s.name, count(r) AS cites
ORDER BY cites DESC LIMIT 10

-- Find hub nodes (high in-degree)
MATCH (n)<-[r]-()
RETURN n.id, n.type, count(r) AS inDegree
ORDER BY inDegree DESC LIMIT 20

-- Walk supersedes chain backwards from current ADR
MATCH p=(current:ADR {id: 'ADR-046'})-[:supersedes*]->(ancestor:ADR)
RETURN [n IN nodes(p) | n.title]

-- Cycle detection (worth a warning)
MATCH p=(n)-[:caused*1..5]->(n)
RETURN p LIMIT 5

Safety

The agentdb_causal_query tool accepts arbitrary Cypher, including writes (CREATE, DELETE, DETACH DELETE). For destructive operations, prefer the typed delete tools (agentdb_causal_node_delete, agentdb_causal_edge_delete) — they enforce cascade semantics and write to the attestation log.

Don't

  • Don't use string interpolation for ids — use params to avoid Cypher injection.
  • Don't run MATCH (n) DETACH DELETE n (deletes everything). Always scope the match.
  • Don't loop a Cypher query in client code when one query with WHERE id IN [...] works — the binding's per-call overhead adds up.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

中文简介正在准备中。当前显示原文说明。

ruvnet/agentdb942026年10月12日 更新

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

中文简介正在准备中。当前显示原文说明。

ruvnet/agentdb942026年10月12日 更新

Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

中文简介正在准备中。当前显示原文说明。

ruvnet/agentdb942026年10月12日 更新

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

中文简介正在准备中。当前显示原文说明。

ruvnet/agentdb942026年10月12日 更新

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

中文简介正在准备中。当前显示原文说明。

ruvnet/agentdb942026年10月12日 更新

Walk the causal graph in AgentDB to explain why two memories are connected, or trace a root cause. Use when the user asks "why did X happen", "what led to Y", or after an incident.

中文简介正在准备中。当前显示原文说明。

ruvnet/agentdb942026年10月12日 更新

查看 ruvnet 的全部技能

报告此技能的问题