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recipe-scout食谱侦察员

Agent Skill

recipe-scout 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

7,128

周安装

297

GitHub Stars

1

下载量

2,376
OpenClaw

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

MIT-0

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:recipe-scout(食谱侦察员)
来源仓库:https://github.com/cylqqqcyl/recipe-scout
安装命令:
openclaw skills install recipe-scout
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install recipe-scout

简介

用于查找、检索和筛选相关信息,适合根据关键词快速定位结果。

  • 可从结构化来源查找并标准化中国菜谱。recipe-scout 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 将干净菜谱注释导出到 Obsidian markdown 笔记。
  • 通过 clawhub 安装,建议确认权限范围和维护状态。
  • 需注意是否会触发联网、命令执行或文件读写操作。

SKILL.md

name
recipe-scout
description
>
user-invocable
true
metadata
{"openclaw":{"emoji":"🥢","homepage":"https://docs.openclaw.ai/tools/skills"}}

recipe-scout

Source-policy + normalization layer for Chinese recipes. Not a single-site scraper.

Source Ranking (strict priority)

Tier A — Structured recipe pages (primary)

  • 下厨房 (xiachufang.com) — largest Chinese UGC recipe platform, step-by-step photos, strong search
  • 美食天下 (meishichina.com) — broad category coverage, reliable ingredient lists
  • 豆果美食 (douguo.com) — large recipe app ecosystem
  • HowToCook (github.com/Anduin2017/HowToCook) — programmer-authored, precise gram-level measurements, no fluff; raw URLs: https://raw.githubusercontent.com/Anduin2017/HowToCook/master/dishes/<category>/<dish>/<dish>.md; categories: meat_dish, aquatic, vegetable_dish, staple, soup, dessert, condiment
  • Reputable cooking blogs with full recipe text

Tier B — Video + transcript (secondary)

  • YouTube / Bilibili cooking videos with captions or clear on-screen ingredients

Tier C — Social posts (fallback / inspiration only)

  • 小红书, short-post platforms, comment threads
  • Mark confidence low unless validated by another source
  • Do NOT treat as authoritative recipe specs
Anti-pattern: Do not make 小红书 the primary recipe backend. UI changes often, ingredient/timing details are frequently missing, extraction is brittle.

Retrieval Strategy

  1. Parse dish intent + constraints (cuisine, diet, equipment, time, restrictions)
  2. Search Tier A first with Chinese queries (see references/query-examples.md)
  3. Collect 3–7 candidates
  4. Deduplicate by core technique + ingredient profile
  5. Rank by: completeness → clarity → home-cooking fit → ingredient accessibility
  6. Use Tier B/C only to fill gaps or add variants

Normalization Rules

  • Language: Chinese default (English if user requests)
  • Units: metric preferred (g / ml / tbsp / tsp); preserve source units if conversion uncertain
  • Times: separate prep / cook / total; mark missing estimates as estimated: true
  • Seasoning: keep exact source values; record 适量 as-is with a practical note
  • Heat: normalize to 小火 / 中小火 / 中火 / 中大火 / 大火
  • Safety: include basic food safety notes (chicken/pork doneness, etc.) when relevant

Anti-Hallucination

  • Never fabricate ingredient quantities, temperatures, or timings
  • Missing fields → unknown / 未注明
  • Clearly distinguish: source facts vs inferred estimates vs your recommendations

Output Modes

ModeWhenOutput
Quick answerCasual askTop 3 options, recommended version, concise steps + shopping list
Structured packUser wants detailNormalized recipe using schema
Obsidian exportCollection/saveOne .md file per recipe → /home/node/vault/Recipes/Chinese/; fallback: {workspace}/exports/recipes/

Schema: See references/schema.md Obsidian template: See references/obsidian-template.md

Execution Playbook

When invoked:

  1. Restate target dish + constraints in one line
  2. Search Tier A with Chinese queries
  3. Return candidate table (3–7): source | completeness | style | confidence
  4. Pick one "default cooking path"
  5. Normalize into canonical schema
  6. Output quick summary in chat
  7. If export requested → write Obsidian note(s), return file paths

Browser vs Web Tools

  • Prefer: web_search (Brave Search API) + web_fetch for structured recipe pages — this is the primary retrieval method
  • Brave Search tip: Use Chinese queries for Tier A sources (下厨房, 豆果, 美食天下); English queries for fallback/Tier B
  • Use browser only when: page requires JS rendering, login/session, or video transcript interaction
  • If Chrome relay is unstable → switch to openclaw browser profile

Hard No's

  • No aggressive scraping
  • No paywall/login bypass
  • No social-media hearsay presented as precise recipe specs
  • No invented measurements

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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

OpenClaw

83.86%
按下载量换算1,993

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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