Files
market/skills/web-access/SKILL.zh-CN.md
Yige 1f7c8b9673 feat: skills i18n 改造(schemaVersion 1.1,零向后兼容) (#1)
* feat: skills i18n 改造 — schemaVersion 1.1,零向后兼容

把 21 个 skills + 1 个 agent + manifest/categories 全量迁移到 schemaVersion 1.1
的 i18n 结构,配套 CI AI 翻译流水线(GitHub Models)与本地工具链。

## 关键变更

### 数据结构(破坏性,schemaVersion 1.0 → 1.1)
- SKILL.md: 顶层 name 改为 ASCII slug(== 目录名,符合 agentskills.io 规范);
  中文显示名/short_desc/description 全部迁入 metadata.i18n.<locale>
- agents/<id>/agent.json: shortDesc/fullDesc/tags/persona.{role,traits} 迁入
  i18n.<locale>;changelog[].changes 改为 { <locale>: string[] } 对象
- categories.json: 每个分类的 label/description 迁入 i18n.<locale>,顶层只剩
  color/icon
- manifest.json: 加 supportedLocales / defaultLocale;顶层 description 迁入
  i18n.<locale>

### Body 文件结构
- 根 SKILL.md = frontmatter + default_locale (en-US) body
- SKILL.<locale>.md = 各 locale 的 markdown body(首行 <!-- locale: xx --> 自校验)

### 工具链(scripts/i18n/)
- glossary.json: zh→en 术语表 + do_not_translate 白名单
- schema/skill-frontmatter.schema.json: i18n frontmatter JSON Schema
- validate-i18n.py: 8 条校验规则(name 合规 / locale 完整性 / hash 一致性等)
- translate.py: GitHub Models / Anthropic 双 backend,sha256 增量翻译
- migrate.py: 一次性迁移脚本(旧格式 → i18n 结构)

### CI(.github/workflows/)
- i18n-validate.yml: PR 触发跑 validate + translate --check
- i18n-translate.yml: PR 触发用 GitHub Models(默认 openai/gpt-5-mini)翻译缺失
  locale,自动追加 commit;可切到 ANTHROPIC_API_KEY 走 Claude

### 文档
- docs/I18N.md: 作者贡献指南(schema 说明 / 提交流程 / 常见问题)
- README.md: 加多语言段落

## 验证

- uv run scripts/i18n/validate-i18n.py: OK,49 文件 0 错误
- uv run scripts/i18n/translate.py --check: 0 stale locale
- 21 skills 标题数 zh-CN == en-US 严格对齐(最大 66=66)
- skills-ref 规范校验:全部通过(顶层 name ASCII slug + description 单字段)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(i18n): 修复 PR #1 review 反馈的 6 项问题

- schema: translated_by 正则放宽为 ^(human|ai:[A-Za-z0-9._:/-]+)$,接受
  'ai:github:openai/gpt-5-mini' 这类 backend:model 形式(CI 翻译输出格式)
- README + docs/I18N.md: 修正"CI 用 Claude API"误导描述,正确说明默认是
  GitHub Models(openai/gpt-5-mini)+ GITHUB_TOKEN,可选切到 Anthropic
- skills/minimax-tts/SKILL.md & SKILL.zh-CN.md: 删除多余的 ``` 闭合,避免
  Markdown 后续渲染错乱
- skills/docx/SKILL.md: 翻译时丢失的 • Unicode escape 示例已恢复,
  与 zh-CN 版本对齐

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-05 00:26:33 +08:00

12 KiB
Raw Blame History

web-access 技能

L0一句话摘要

三层联网访问工具包——搜索公开页面、Jina 优化抓取、CDP 登录态浏览器访问。

L1概述与使用场景

能力描述

web-access 是一个流程型技能Procedural Skill提供三层互补的联网访问能力Layer 1WebSearch + WebFetch用于公开页面Layer 2Jina Reader用于 JS 渲染的重页面,默认节省 TokenLayer 3Chrome CDP用于需要登录态的站点小红书/B站/微博/飞书/Twitter

使用场景

  • 用户需要搜索当前信息或研究特定主题
  • 用户需要抓取公开网页内容或技术文档
  • 用户需要访问登录态站点小红书、B站、微博、飞书、Twitter 等)
  • 用户需要对比产品、聚合新闻或调查 API/库版本

核心价值

  • 三层递进:从轻量搜索到重度 JS 渲染到登录态访问,按需选择
  • Token 优化Jina Reader 默认减少 50-80% Token 消耗
  • 登录态复用:通过 CDP 连接用户已登录的 Chrome无需重复登录

L2详细规范

Output Rule

When you complete a research task, you MUST cite all source URLs in your response. Distinguish between:

  • Quoted facts: directly from a fetched page → cite the URL
  • Inferences: your synthesis or analysis → mark as "(分析/推断)"

If any fetch fails, explicitly tell the user which URL failed and which fallback you used.


Prerequisites: Chrome CDP Setup (for login-gated sites)

Only required when accessing sites that need the user's login session (小红书/B站/微博/飞书/Twitter/知乎/公众号).

One-time setup

Launch a dedicated Chrome instance with remote debugging enabled:

macOS:

/Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome \
  --remote-debugging-port=9222 \
  --user-data-dir="$HOME/.desirecore/chrome-profile"

Linux:

google-chrome \
  --remote-debugging-port=9222 \
  --user-data-dir="$HOME/.desirecore/chrome-profile"

Windows (PowerShell):

& "C:\Program Files\Google\Chrome\Application\chrome.exe" `
  --remote-debugging-port=9222 `
  --user-data-dir="$env:USERPROFILE\.desirecore\chrome-profile"

After launch:

  1. Manually log in to the sites you need (小红书、B站、微博、飞书 …)
  2. Leave this Chrome window open in the background
  3. Verify the debug endpoint: curl -s http://localhost:9222/json/version should return JSON

Verify CDP is ready

Before any CDP operation, always run:

curl -s http://localhost:9222/json/version | python3 -c "import sys,json; d=json.load(sys.stdin); print('CDP ready:', d.get('Browser'))"

If the command fails, tell the user: "请先启动 Chrome 并开启远程调试端口(见 web-access 技能的 Prerequisites 部分)。"


Tool Selection Decision Tree

User intent
  │
  ├─ "Search for information about X" (no specific URL)
  │     └─→ WebSearch → pick top 3-5 results → fetch each (see next branches)
  │
  ├─ "Read this public page" (static HTML, docs, news)
  │     └─→ WebFetch(url) directly
  │
  ├─ "Read this heavy-JS page" (SPA, React/Vue sites, Medium, etc.)
  │     └─→ Bash: curl -sL "https://r.jina.ai/<original-url>"
  │          (Jina Reader = default for JS-rendered content, saves tokens)
  │
  ├─ "Read this login-gated page" (小红书/B站/微博/飞书/Twitter/知乎/公众号)
  │     └─→ 1. Verify CDP ready (curl http://localhost:9222/json/version)
  │          2. Bash: python3 script with playwright.connect_over_cdp()
  │          3. Extract content → feed to Jina Reader for clean Markdown
  │             (or use BeautifulSoup directly on the raw HTML)
  │
  ├─ "API documentation / GitHub / npm package info"
  │     └─→ Prefer official API endpoints over scraping HTML:
  │          - GitHub: gh api repos/owner/name
  │          - npm:    curl https://registry.npmjs.org/<pkg>
  │          - PyPI:   curl https://pypi.org/pypi/<pkg>/json
  │
  └─ "Real-time interactive task" (click, fill form, scroll, screenshot)
        └─→ CDP + Playwright (see references/cdp-browser.md)

Three-layer strategy summary

Layer Use case Primary tool Token cost
L1 Public, static WebFetch Low
L2 JS-heavy, long articles, token savings Bash curl r.jina.ai Lowest (Markdown pre-cleaned)
L3 Login-gated, interactive Bash + Python Playwright CDP Medium (raw HTML, then clean via Jina or BS4)

Default priority: L1 for simple public pages → L2 for anything heavy → L3 only when login is required.


Supported Sites Matrix

Site Recommended Layer Notes
Wikipedia, MDN, official docs L1 WebFetch Static, clean HTML
GitHub README, issues, PRs gh api (best) → L1 WebFetch Prefer API
Hacker News, Reddit L1 WebFetch Public content
Medium, Dev.to L2 Jina Reader JS-rendered, member gates
Twitter/X L3 CDP (or L2 Jina with x.com) Login required for full thread
小红书 (xiaohongshu.com) L3 CDP 强制登录
B站 (bilibili.com) L3 CDP 视频描述/评论需登录
微博 (weibo.com) L3 CDP 长微博需登录
知乎 (zhihu.com) L3 CDP 长文+评论需登录
飞书文档 (feishu.cn) L3 CDP 必须登录
公众号 (mp.weixin.qq.com) L2 Jina Reader 通常公开Jina 处理更干净
LinkedIn L3 CDP 登录墙

Tool Reference

Layer 1: WebSearch + WebFetch

WebSearch — discover URLs for an unknown topic:

WebSearch(query="latest typescript 5.5 features 2026", max_results=5)

Tips:

  • Include the year for time-sensitive topics
  • Use allowed_domains / blocked_domains to constrain

WebFetch — extract clean Markdown from a known URL:

WebFetch(url="https://example.com/article")

Tips:

  • Results cached for 15 min
  • Returns cleaned Markdown with title + URL + body
  • If body < 200 chars or looks garbled → escalate to Layer 2 (Jina) or Layer 3 (CDP)

Layer 2: Jina Reader (default for heavy pages)

Jina Reader (r.jina.ai) is a free public proxy that renders pages server-side and returns clean Markdown. Use it as the default for any page where WebFetch produces garbled or truncated output, and as the preferred extractor for JS-heavy SPAs.

curl -sL "https://r.jina.ai/https://example.com/article"

Why Jina is the default token-saver:

  • Strips nav/footer/ads automatically
  • Handles JS-rendered SPAs
  • Returns 50-80% fewer tokens than raw HTML
  • No API key needed for basic use (~20 req/min)

See references/jina-reader.md for advanced endpoints and rate limits.

Layer 3: CDP Browser (login-gated access)

Use Python Playwright's connect_over_cdp() to attach to the user's running Chrome (which already has login cookies). No re-login needed.

Minimal template:

python3 << 'PY'
from playwright.sync_api import sync_playwright

TARGET_URL = "https://www.xiaohongshu.com/explore/..."

with sync_playwright() as p:
    browser = p.chromium.connect_over_cdp("http://localhost:9222")
    context = browser.contexts[0]  # reuse user's default context (has cookies)
    page = context.new_page()
    page.goto(TARGET_URL, wait_until="domcontentloaded")
    page.wait_for_timeout(2000)  # let lazy content load
    html = page.content()
    page.close()

# Print first 500 chars to verify
print(html[:500])
PY

Extract text via BeautifulSoup (no Jina round-trip):

python3 << 'PY'
from playwright.sync_api import sync_playwright
from bs4 import BeautifulSoup

with sync_playwright() as p:
    browser = p.chromium.connect_over_cdp("http://localhost:9222")
    page = browser.contexts[0].new_page()
    page.goto("https://www.bilibili.com/video/BV...", wait_until="networkidle")
    html = page.content()
    page.close()

soup = BeautifulSoup(html, "html.parser")
title = soup.select_one("h1.video-title")
desc = soup.select_one(".video-desc")
print("Title:", title.get_text(strip=True) if title else "N/A")
print("Desc:",  desc.get_text(strip=True)  if desc  else "N/A")
PY

See references/cdp-browser.md for:

  • Per-site selectors (小红书/B站/微博/知乎/飞书)
  • Scrolling & lazy-load patterns
  • Screenshot & form-fill recipes
  • Troubleshooting connection issues

Common Workflows

Read references/workflows.md for detailed templates:

  • 技术文档查询 (Tech docs lookup)
  • 竞品对比研究 (Competitor research)
  • 新闻聚合与时间线 (News aggregation)
  • API/库版本调查 (Library version investigation)

Read references/cdp-browser.md for login-gated site recipes (小红书/B站/微博/知乎/飞书).

Read references/jina-reader.md for Jina Reader positioning, rate limits, and advanced endpoints.


Quick Workflow: Multi-Source Research

1. WebSearch(query) → 5 candidate URLs
2. Skim titles + snippets → pick 3 most relevant
3. Classify each URL by layer (L1 / L2 / L3)
4. Fetch all in parallel (single message, multiple tool calls)
5. If any fetch returns < 200 chars or garbled → retry via next layer
6. Synthesize: contradictions? consensus? outliers?
7. Report with inline [source](url) citations + a Sources list at the end

Anti-Patterns (Avoid)

  • Using WebFetch on obviously heavy sites — Medium, Twitter, 小红书 will waste tokens or fail. Jump straight to L2/L3.
  • Launching headless Chrome instead of CDP attach — loses user's login state, triggers anti-bot, slow cold start. Always use connect_over_cdp() to attach to the user's existing session.
  • Fetching one URL at a time when you need 5 — batch in a single message.
  • Trusting a single source — cross-check ≥ 2 sources for non-trivial claims.
  • Fetching the search result page itself — WebSearch already returns snippets; fetch the actual articles.
  • Ignoring the cache — WebFetch caches 15 min, reuse freely.
  • Scraping when an API exists — GitHub, npm, PyPI, Wikipedia all have JSON APIs.
  • Forgetting the year in time-sensitive queries — "best AI models" returns 2023 results; "best AI models 2026" returns current.
  • Hardcoding login credentials in scripts — always rely on the user's pre-logged CDP session.
  • Citing only after the fact — collect URLs as you fetch, not from memory afterwards.

Example Interaction

User: "帮我抓一下这条小红书笔记的内容:https://www.xiaohongshu.com/explore/abc123"

Agent workflow:

1. 识别 → 小红书是 L3 登录态站点
2. 检查 CDPcurl -s http://localhost:9222/json/version
   ├─ 失败 → 提示用户启动 Chrome 调试模式,终止
   └─ 成功 → 继续
3. Bash: python3 connect_over_cdp 脚本 → page.goto(url) → page.content()
4. BeautifulSoup 提取 h1 title、.note-content、.comments
5. 返回给用户时:
   - 引用原 URL
   - 若内容很长,用 Jina 清洗一遍节省 token
6. 告知用户:「已通过你的登录态抓取,原链接:[xhs](url)」

Installation Note

CDP features require Python + Playwright installed:

pip3 install playwright beautifulsoup4
python3 -m playwright install chromium  # only needed if user hasn't installed Chrome

If playwright is not installed when the user requests a login-gated site, run the install commands in Bash and explain you're setting up the browser automation dependency.