Agent Skillszerogpu/zerogpu-router › extract-entities

extract-entities

GitHub

基于gliner2-base-v1模型,通过ZeroGPU API执行自定义标签的命名实体识别。支持提取人员、组织、地点等用户定义类型的实体,需指定标签并可选设置置信度阈值,适用于从文本中抽取结构化信息。

agents/openclaw/plugin/skills/extract-entities/SKILL.md zerogpu/zerogpu-router

Trigger Scenarios

需要从文本中提取特定类型的实体(如人名、公司名) 用户要求使用自定义标签进行命名实体识别 请求分析文本中的组织机构或日期等信息

Install

npx skills add zerogpu/zerogpu-router --skill extract-entities -g -y
More Options

Non-standard path

npx skills add https://github.com/zerogpu/zerogpu-router/tree/main/agents/openclaw/plugin/skills/extract-entities -g -y

Use without installing

npx skills use zerogpu/zerogpu-router@extract-entities

指定 Agent (Claude Code)

npx skills add zerogpu/zerogpu-router --skill extract-entities -a claude-code -g -y

安装 repo 全部 skill

npx skills add zerogpu/zerogpu-router --all -g -y

预览 repo 内 skill

npx skills add zerogpu/zerogpu-router --list

SKILL.md

Frontmatter
{
    "name": "extract-entities",
    "metadata": {
        "openclaw": {
            "install": [
                {
                    "bins": [
                        "zerogpu"
                    ],
                    "kind": "node",
                    "package": "zerogpu-cli"
                }
            ],
            "requires": {
                "bins": [
                    "zerogpu"
                ]
            }
        }
    },
    "description": "Custom-label named-entity recognition (gliner2-base-v1). Use when the user wants to extract entities with their own labels — people, organizations, locations, products, dates, or any caller-defined entity types — from a passage.",
    "allowed-tools": "Bash(zerogpu extract_entities*)",
    "argument-hint": "<text> (-l <label>... | --labels a,b,c) [-t <0..1>]"
}

Sends your input to ZeroGPU's hosted API for inference — this is not local processing. Don't pass secrets, credentials, or regulated data you aren't cleared to share with a third party. See the plugin README's "Data & privacy" section.

Run custom-label NER:

zerogpu extract_entities $ARGUMENTS

Quoting (required, to survive shell parsing of arbitrary user text): format $ARGUMENTS with the source text wrapped via heredoc command substitution, then flags after. Inside the heredoc, paste the user's text verbatim — do not escape:

"$(cat <<'ZGPU_T'
<the source text, verbatim, multi-line and special chars all OK>
ZGPU_T
)" --labels person,company,date [-t 0.3]

At least one -l <label> (or --labels a,b,c) is required. Optional -t <threshold> filters spans below a confidence (default 0.3, must be in [0, 1]).

Savings note: only if the command output literally contains a line starting with 💰 ZeroGPU savings, append that exact line, unchanged, as the last line of your reply. If no such line is present, say nothing about savings and do not mention or suggest the cost-savings skill — this note is intentionally occasional, not shown every time.

Version History

  • cee9321 Current 2026-08-02 21:15

    更新依赖库并修复安全漏洞

  • 7b9b503 2026-07-24 11:48

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Metadata

Files
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Version
cee9321
Hash
a3df95e8
Indexed
2026-07-24 11:48

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