extract-entities

Agent Skills › zerogpu/zerogpu-router › extract-entities

extract-entities

GitHub

调用ZeroGPU API执行自定义标签命名实体识别，从文本中提取用户指定类型的实体信息。

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用户要求使用自定义标签进行NER

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 chat_completions *)",
    "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. The user gives the source text and the entity labels, as flags (-l person -l company, --labels person,company, -t 0.4) or in plain words.

Run this with the exec tool, filling in the labels and pasting the source text into the heredoc verbatim — no escaping, the quoted heredoc handles every shell metacharacter, newline, quote, and paren:

zerogpu chat_completions -m gliner2-base-v1 --metadata '{"usecase":"ner","labels":["person","company"],"threshold":0.3}' <<'ZGPU_END_OF_INPUT'
<the source text, verbatim>
ZGPU_END_OF_INPUT

"usecase":"ner" is required exactly as written; the API rejects the request without it.
labels needs at least one label. If the user names none, ask which entity types to extract.
threshold is the minimum confidence in [0, 1]. Use 0.3 unless the user gives one.
--metadata is single-quoted JSON, so write any ' inside a label as '\''.

Output is a JSON object whose entities maps each label to the spans found.

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

4e1b070 Current 2026-09-22 08:08
升级至v4.4.0，改为调用zerogpu-cli模型无关端点，技能体转为exec工具指令，依赖CLI版本3.8.0及以上。
cee9321 2026-08-02 21:15
更新依赖库并修复安全漏洞
7b9b503 2026-07-24 11:48

Metadata

Files: 0
Version: 4e1b070
Hash: 0785e7c4
Indexed: 2026-07-24 11:48

extract-entities