← 返回 Skills 市场
fisa712

my skill -names

作者 Muhammad Asif · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
76
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install tigergraph-connector
功能描述
Connect to TigerGraph distributed graph database to query, load, and manage large-scale knowledge graph data using GSQL and REST++ APIs
安全使用建议
This package claims to be a production TigerGraph connector but has several red flags: the source/publisher is unknown and the registry name doesn't match the internal project name; documentation advertises a real connector while the included Python file uses simulated/mock methods rather than performing real network operations; and the skill describes needing an API token/credentials but none are declared in the registry metadata. Before installing or giving credentials: (1) ask the publisher for provenance and a proper homepage/repo; (2) review the Python code yourself—note that run_query currently calls a mock method that returns dummy results; (3) do not provide API tokens or passwords until you confirm the skill actually uses a legitimate TigerGraph client and communicates with expected endpoints; (4) if you still want to test it, run it in an isolated environment and avoid exposing production credentials; (5) request or require an update that either implements real client calls (with clear dependency instructions) or explicitly documents that the current implementation is a stub/mock.
功能分析
Type: OpenClaw Skill Name: testing-kggggg123 Version: 1.0.0 The TigerGraph Connector skill bundle is a legitimate and well-documented integration for interacting with TigerGraph databases. The Python implementation in `scripts/tigergraph_connector.py` provides a structured interface for GSQL queries and graph operations using standard libraries and safe coding practices. The documentation in `SKILL.md` and `README.md` is comprehensive, providing clear instructions and examples for graph data management without any indicators of malicious intent, data exfiltration, or prompt injection vulnerabilities.
能力标签
cryptocan-make-purchases
能力评估
Purpose & Capability
The SKILL.md, README and code all describe a TigerGraph connector (GSQL + REST++ capabilities). That purpose is consistent across files. However the registry metadata name ('my skill -names') doesn't match the internal name ('tigergraph_connector') and the publisher/source is unknown — a minor coherence issue but not by itself critical.
Instruction Scope
The documentation and examples describe live operations (connecting to a TigerGraph instance, running queries, loading CSVs). The included Python script, however, uses simulated/mock execution (e.g., _mock_query_execution and a connect() that 'simulates' a connection) and does not actually import or call a TigerGraph client. This inconsistency between 'production-ready' claims and the actual runtime behavior is misleading and could surprise users expecting real network interactions.
Install Mechanism
There is no install spec (instruction-only), which is low risk. README suggests installing pyTigerGraph (pip install pyTigerGraph) but the provided code does not depend on it. Absence of a formal install step is coherent for an instruction-only skill, but the mismatch between README guidance and the code's simulated implementation is a documentation/code inconsistency to be aware of.
Credentials
The SKILL.md describes connection parameters that include an api_token, username, and password, but the skill metadata declares no required environment variables or primary credential. That by itself isn't fatal (credentials may be supplied at runtime), but it's an inconsistency: the skill requires sensitive credentials to perform useful work yet doesn't declare them in metadata. Users should not assume the registry will manage credentials safely.
Persistence & Privilege
No persistent or elevated privileges are requested: always is false, there is no install spec writing files, and the skill does not declare config paths or system-level access. Autonomous invocation is allowed by default (normal) but there are no additional persistence flags.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install tigergraph-connector
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /tigergraph-connector 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
TigerGraph Connector skill 1.0.0 initial release: - Enables connection to TigerGraph distributed graph database using GSQL and REST++ APIs. - Supports querying, data loading (vertices/edges), and schema management for large-scale knowledge graphs. - Provides built-in and custom graph algorithm execution (e.g., PageRank, community detection). - Offers sample configuration, data-loading patterns, and error-handling guidance. - Includes documentation for GSQL, REST++ usage, and best practices for enterprise-scale graph analytics.
元数据
Slug tigergraph-connector
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

my skill -names 是什么?

Connect to TigerGraph distributed graph database to query, load, and manage large-scale knowledge graph data using GSQL and REST++ APIs. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 76 次。

如何安装 my skill -names?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install tigergraph-connector」即可一键安装,无需额外配置。

my skill -names 是免费的吗?

是的,my skill -names 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

my skill -names 支持哪些平台?

my skill -names 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 my skill -names?

由 Muhammad Asif(@fisa712)开发并维护,当前版本 v1.0.0。

💬 留言讨论