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feed-diet饲料饮食

Agent Skill

feed-diet 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

19,151

周安装

806

GitHub Stars

公开资料未说明

下载量

6,706
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:feed-diet(饲料饮食)
来源仓库:https://github.com/tkuehnl/feed-diet
安装命令:
openclaw skills install feed-diet
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 feed-diet

简介

通过 HN 和 RSS 源审核您的信息饮食 — 包含类别细分、ASCII 图表和个性化推荐的精美报告。

SKILL.md

name
feed-diet
version
0.1.1
description
Audit your information diet across HN and RSS feeds — beautiful reports with category breakdowns, ASCII charts, and personalized recommendations.
author
Anvil AI
tags
[productivity, reading, analysis, hacker-news, rss, information-diet, discord, discord-v2]

🍽️ Feed Diet

Audit your information diet and get a gorgeous report showing what you actually consume.

Trigger

Activate when the user mentions any of:

  • "feed diet"
  • "information diet"
  • "audit my feeds"
  • "what am I reading"
  • "analyze my HN"
  • "reading habits"
  • "content diet"
  • "feed report"

Instructions

Audit Mode (default)

  1. Determine the data source. Ask the user for one of:

- A Hacker News username (e.g., "tosh") - An OPML file path containing RSS feed subscriptions

  1. Fetch the content. Run the appropriate fetch script:
   # For HN:
   bash "$SKILL_DIR/scripts/hn-fetch.sh" USERNAME 100
   
   # For OPML:
   bash "$SKILL_DIR/scripts/opml-parse.sh" /path/to/feeds.opml
  1. Classify items. Pipe the fetched items through the classifier:
   cat items.jsonl | bash "$SKILL_DIR/scripts/classify.sh" > classified.jsonl

The classifier uses LLM (if ANTHROPIC_API_KEY or OPENAI_API_KEY is set) or falls back to keyword matching.

  1. Generate the report. Run the main entry point:
   bash "$SKILL_DIR/scripts/feed-diet.sh" audit --hn USERNAME --limit 100
  1. Present the report to the user. The output is Markdown — render it directly.

Digest Mode (weekly curated reading)

When the user wants a filtered reading list based on their goals:

bash "$SKILL_DIR/scripts/feed-diet.sh" digest --hn USERNAME --goal "systems programming, distributed systems" --days 7

Quick Reference

CommandDescription
feed-diet audit --hn USERFull diet audit for an HN user
feed-diet audit --opml FILEFull diet audit from RSS feeds
feed-diet digest --hn USER --goal "X"Weekly digest filtered by goals

Notes for the Agent

  • Be conversational. After presenting the report, offer observations like "Looks like you're heavy on news — want me to suggest some deeper technical feeds?"
  • Suggest the digest mode if the user seems interested in filtering their reading.
  • The report is the star. Don't summarize it — present it in full. It's designed to be screenshot-worthy.
  • If classification seems off, mention that setting an LLM API key improves accuracy.

Discord v2 Delivery Mode (OpenClaw v2026.2.14+)

When the conversation is happening in a Discord channel:

  • Send a compact first summary (top category, diversity score, top 2 recommendations), then ask if the user wants the full report.
  • Keep the first response under ~1200 characters and avoid wide category tables in the first message.
  • If Discord components are available, include quick actions:

- Show Full Diet Report - Generate Weekly Digest - Show Recommendations

  • If components are not available, provide the same follow-ups as a numbered list.
  • Prefer short follow-up chunks (<=15 lines per message) when sharing long reports.

References

  • scripts/feed-diet.sh — Main entry point
  • scripts/hn-fetch.sh — Hacker News story fetcher
  • scripts/opml-parse.sh — OPML/RSS feed parser
  • scripts/classify.sh — Batch content classifier (LLM + fallback)
  • scripts/common.sh — Shared utilities and formatting

Examples

Example 1: HN Audit

User: "Audit my HN reading diet — my username is tosh"

Agent runs:

bash "$SKILL_DIR/scripts/feed-diet.sh" audit --hn tosh --limit 50

Output: A full Markdown report with category breakdown table, top categories with sample items, surprising finds, and recommendations.

Example 2: Weekly Digest

User: "Give me a digest of what's relevant to my work on compilers and programming languages"

Agent runs:

bash "$SKILL_DIR/scripts/feed-diet.sh" digest --hn tosh --goal "compilers, programming languages, parsers" --days 7

Output: A curated reading list of 10-20 items ranked by relevance to the user's goals.

Example 3: RSS Feed Audit

User: "Here's my OPML file, tell me what my feed diet looks like"

Agent runs:

bash "$SKILL_DIR/scripts/feed-diet.sh" audit --opml /path/to/feeds.opml

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

84.67%
按下载量换算5,678

安全审计

VirusTotal

通过

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通过

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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来源信息

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