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venice-augment威尼斯增强

Agent Skill

venice-augment 用于处理浏览器自动化、网页检查和页面信息提取,适合在 Codex、Claude、Cursor、Gemini CLI 中需要让 Agent 打开页面、读取网页或验证前端流程时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

392

周安装

16

GitHub Stars

35

下载量

125
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:venice-augment(威尼斯增强)
来源仓库:https://github.com/veniceai/skills
仓库路径:skills/venice-augment
安装命令:
npx skills add https://github.com/veniceai/skills --skill venice-augment
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/veniceai/skills --skill venice-augment

简介

用于处理浏览器自动化、网页检查和页面信息提取。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中打开页面、读取网页或验证前端流程时使用。
  • 可结合来源仓库、安装命令和原始 README 继续核验具体用法。
  • 安装方式:github,命令为 npx skills add https://github.com/veniceai/skills --skill venice-augment。
  • 建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

SKILL.md

Venice Augment (text parse / scrape / search)

Three lightweight helpers for agent pipelines that need document text, web pages, or search results without spinning up your own crawler.

EndpointInputOutputPrivacy
POST /augment/text-parsermultipart/form-data file (PDF / DOCX / XLSX / plain text, ≤ 25 MB){text, tokens} JSON or plain textIn-memory only, zero retention
POST /augment/scrape{url}{url, content (markdown), format: "markdown"}Zero retention
POST /augment/search{query, limit?, search_provider?}{query, results: [{title, url, content, date}]}Brave ZDR / Google anonymized; zero retention

All three accept Bearer API key or SIWE (x402 wallet). All three are priced dynamically ($0.001–$10.00).

POST /augment/text-parser — extract text from documents

Request

Always multipart/form-data:

FieldNotes
fileRequired. PDF, DOCX, XLSX, or plain text. Max 25 MB.
response_formatjson (default) or text.
curl -X POST https://api.venice.ai/api/v1/augment/text-parser \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -F "file=@./contract.pdf" \
  -F "response_format=json"

Response

response_format=json:

{
  "text": "…extracted plaintext…",
  "tokens": 3821
}

response_format=text — raw plaintext body (Content-Type: text/plain).

Tips

  • tokens is the count of the extracted text — use it to pre-budget a downstream chat request.
  • Scanned image PDFs are not OCR'd. Run images through a vision model via /chat/completions instead.
  • Documents are processed in memory only and content is not retained after the response. (Operational metadata like request IDs and error traces may still be logged for debugging — this is a no-content-retention guarantee, not a zero-log guarantee.)

POST /augment/scrape — URL → markdown

Request

{ "url": "https://example.com/article" }
curl -X POST https://api.venice.ai/api/v1/augment/scrape \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://example.com"}'

Response

{
  "url": "https://example.com",
  "content": "# Example Domain\n\nThis domain is for use in …",
  "format": "markdown"
}

Tips

  • Blocked sites — X/Twitter and Reddit reject automated access and return 400 immediately. Use enable_x_search or enable_web_search on /chat/completions for those.
  • Some sites may return a partial body. Verify with the returned content length before piping into a model.
  • Use together with /chat/completions: scrape → feed markdown into messages → summarize.
  • For bulk scraping, issue requests in parallel; each is billed independently.

POST /augment/search — web search

Request

FieldNotes
query1–400 chars. Required.
limit1–20. Default 10.
search_provider"brave" (default, ZDR) or "google" (anonymized).
curl -X POST https://api.venice.ai/api/v1/augment/search \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "venice ai api pricing",
    "limit": 5,
    "search_provider": "brave"
  }'

Response

{
  "query": "venice ai api pricing",
  "results": [
    {
      "title": "Pricing — Venice.ai",
      "url": "https://venice.ai/pricing",
      "content": "Venice offers per-token pricing …",
      "date": "2026-04-10"
    }
  ]
}

Providers

ProviderRetentionBias / filter
brave (default)Zero Data Retention — Brave never stores queries.Safesearch defaults, Brave Index.
googleAnonymized — proxied through Venice so Google doesn't see you; Venice doesn't log queries.Google ranking.

Tips

  • Pair with /chat/completions + venice_parameters.enable_web_citations to generate cited answers. See venice-chat.
  • For "search + read" pipelines, feed results[*].url into /augment/scrape in parallel.
  • query is validated as 1–400 chars. Anything longer is rejected (400 INVALID_REQUEST), not truncated.

Errors

StatusCause
400Missing/oversized file, unsupported format, URL on a blocklist (X, Reddit), empty query, query > 400 chars.
401Missing/invalid Bearer or SIWE.
402Insufficient balance. x402 wallets receive the PAYMENT-REQUIRED header with base64 top-up instructions; Bearer users get INSUFFICIENT_BALANCE.
403Unauthorized access.
429Rate limit tripped. Back off with jitter.
500Upstream fetch / parse failure. Safe to retry.

Response headers

  • X-Balance-Remaining — remaining x402 credit (x402 auth only).
  • Content-Encoding — present when Accept-Encoding: gzip, br is sent (text-parser + scrape outputs compress well).

Patterns

  • Document QA — Upload PDF via /augment/text-parser, pass text into a /chat/completions system message, ask questions.
  • Research agent/augment/search → parallel /augment/scrape/chat/completions with all markdown bodies.
  • Data extraction — XLSX via text-parser surfaces tab-delimited cell data you can then pipe to a model with response_format: {type: "json_schema",...}.
  • Citation pipeline — Use /augment/search to pick sources, then give the chat model venice_parameters.enable_web_citations: true for inline [n] marks.

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安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.24%
按下载量换算44

Claude

28.97%
按下载量换算36

Cursor

17.73%
按下载量换算22

Gemini CLI

9.88%
按下载量换算12

安全审计

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通过

Snyk

可疑

权限和风险

敏感数据

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安装前确认

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来源信息

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