← 返回 Skills 市场
79
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install parallel-tfidf-search-workload-balancing
功能描述
Optimize workload distribution across workers, processes, or nodes for efficient parallel execution. Use when asked to balance work distribution, improve par...
安全使用建议
This skill appears coherent and safe: it contains example algorithms and patterns for balancing workloads and asks for no credentials or installs. Before running any provided snippets in your environment, review and test them (they are illustrative and may need adaptation), ensure any referenced network calls (e.g., fetch in the I/O example) point to trusted endpoints, and avoid copying snippets directly into production without standard safety checks (timeouts, input validation, resource limits).
功能分析
Type: OpenClaw Skill
Name: parallel-tfidf-search-workload-balancing
Version: 0.1.0
The skill bundle provides educational and functional code snippets for workload balancing and distributed system patterns, such as consistent hashing, circuit breakers, and work stealing. The implementation uses standard Python libraries (asyncio, concurrent.futures, hashlib) and the instructions in SKILL.md are strictly aligned with the stated purpose of optimizing parallel execution without any indicators of malicious intent or prompt injection. Files analyzed: SKILL.md, references/advanced_techniques.md, and _meta.json.
能力评估
Purpose & Capability
Name/description align with the content: the SKILL.md and references provide standard load‑balancing strategies and helper algorithms. No unrelated libs, credentials, or system access are requested.
Instruction Scope
Runtime instructions and code snippets are limited to partitioning, scheduling, and monitoring logic. They do not direct the agent to read system files, access credentials, or exfiltrate data. Example snippets reference a fetch() in an I/O example but do not instruct external data submission beyond normal network I/O patterns expected for I/O-bound tasks.
Install Mechanism
Instruction-only skill with no install spec and no code files to be executed by the platform; nothing is downloaded or written to disk by an installer.
Credentials
No required environment variables, credentials, or config paths are declared. The strategies shown do not require secrets and the declared requirements are minimal and proportionate.
Persistence & Privilege
always is false and the skill does not request persistent or elevated platform privileges, nor does it modify other skills or system-wide configuration.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install parallel-tfidf-search-workload-balancing - 安装完成后，直接呼叫该 Skill 的名称或使用
/parallel-tfidf-search-workload-balancing触发 - 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
v0.1.0
Bulk publish from all-task-skills-dedup
元数据
常见问题
workload-balancing 是什么？
Optimize workload distribution across workers, processes, or nodes for efficient parallel execution. Use when asked to balance work distribution, improve par... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 79 次。
如何安装 workload-balancing？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install parallel-tfidf-search-workload-balancing」即可一键安装，无需额外配置。
workload-balancing 是免费的吗？
是的，workload-balancing 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
workload-balancing 支持哪些平台？
workload-balancing 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 workload-balancing？
由 lnj22（@lnj22）开发并维护，当前版本 v0.1.0。
推荐 Skills