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Agent Skill · 研究检索

humanize-beagle(比格犬拟人化)

humanize-beagle 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

humanize-beagle 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 64,379。

总安装 303周安装 13GitHub Stars 54下载 106核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:humanize-beagle(比格犬拟人化)
来源仓库:https://github.com/existential-birds/beagle
仓库路径:skills/humanize-beagle
安装命令:
npx skills add https://github.com/existential-birds/beagle --skill humanize-beagle
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/existential-birds/beagle --skill humanize-beagle

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

humanize-beagle 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景从来源线索中提取内容的场景。通过命令行安装并使用,支持预览模式和分类筛选功能。使用前需确认权限范围和维护状态,注意可能触发联网或文件操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/humanize-beagle

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/existential-birds/beagle --skill humanize-beag…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

humanize-beagle 怎么安装?

在终端执行 npx skills add https://github.com/existential-birds/beagle --skill humanize-beagle。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

humanize-beagle 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

humanize-beagle 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

humanize-beagle 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

humanize-beagle 用的人多吗?

公开数据是累计安装 303 次,近一周安装 13 次,下载 106 次,GitHub 54 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

humanize-beagle 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
humanize-beagle

比格犬拟人化 · 本页

30354需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Humanize

Apply fixes from a previous review-ai-writing run with automatic safe/risky classification.

Usage

/beagle-docs:humanize-beagle [--dry-run] [--all] [--category <name>]

Flags:

  • --dry-run - Show what would be fixed without changing files
  • --all - Fix entire codebase (runs review with --all first)
  • --category <name> - Only fix specific category: content|vocabulary|formatting|communication|filler|code_docs

Instructions

1. Parse Arguments

Extract flags from $ARGUMENTS:

  • --dry-run - Preview mode only
  • --all - Full codebase scan
  • --category <name> - Filter to specific category

2. Pre-flight Safety Checks

# Check for uncommitted changes
git status --porcelain

If working directory is dirty, warn:

Warning: You have uncommitted changes. Creating a git stash before proceeding.
Run `git stash pop` to restore if needed.

Create stash if dirty:

git stash push -u -m "beagle-docs: pre-humanize backup"

3. Load Review Results

Check for existing review file:

cat .beagle/ai-writing-review.json 2>/dev/null

If file missing:

  • If --all flag: Run /beagle-docs:review-ai-writing --all first
  • Otherwise: Fail with: "No review results found. Run /beagle-docs:review-ai-writing first."

If file exists, validate freshness:

# Get stored git HEAD from JSON
stored_head=$(jq -r '.git_head' .beagle/ai-writing-review.json)
current_head=$(git rev-parse HEAD)

if [ "$stored_head" != "$current_head" ]; then
  echo "Warning: Review was run at commit $stored_head, but HEAD is now $current_head"
fi

If stale, prompt: "Review results are stale. Re-run review? (y/n)"

4. Load Reference Material

Read the appropriate reference files based on the findings being fixed:

  • Read references/vocabulary-swaps.md when applying ai_vocabulary_high or ai_vocabulary_low fixes
  • Read references/fix-strategies.md for strategy details and before/after examples for any category
  • Read references/developer-voice.md for tone/register guidance when rewriting prose

Only load what you need — if fixing only vocabulary, skip the voice guide.

5. Filter Findings

If --category is set, filter findings to that category only.

Partition remaining findings by fix_safety:

Safe Fixes (auto-apply):

  • chat_leak - Delete conversational artifacts
  • cutoff_disclaimer - Delete knowledge cutoff references
  • filler_phrase - Delete filler phrases
  • heading_restatement - Delete restating first sentence
  • emoji_decoration - Remove emoji from technical text
  • boldface_overuse - Remove excessive bold formatting
  • ai_vocabulary_high - Swap high-signal AI words
  • narrating_obvious - Delete obvious code comments
  • synthetic_opener - Delete "In today's..." openers
  • sycophantic_tone - Delete or neutralize praise
  • vague_authority - Delete unattributed claims
  • excessive_hedging - Remove qualifiers
  • generic_conclusion - Delete summary padding
  • copula_avoidance - Use "is/are" naturally
  • rhetorical_device - Delete rhetorical questions
  • em_dash_overuse - Replace formulaic em dashes with commas, parentheses, or colons
  • thematic_break - Remove horizontal rules before headings
  • title_case_heading - Convert AI title-case headings to sentence case
  • curly_quotes - Normalize curly quotes/apostrophes to straight
  • negative_parallelism - Delete "Not just X, but also Y" filler constructions
  • challenges_and_prospects - Delete "Despite its... faces challenges..." formulaic wrappers

Needs Review Fixes (require confirmation):

  • promotional_language - Rewrite with specifics
  • formulaic_structure - Restructure sections
  • synonym_cycling - Pick consistent term
  • commit_inflation - Rewrite commit scope
  • tautological_docstring - Rewrite or delete docstring
  • exhaustive_enumeration - Trim parameter docs
  • this_noun_verbs - Rewrite docstring voice
  • ai_vocabulary_low - Reduce cluster density
  • apologetic_error - Rewrite error message
  • rule_of_three - Simplify three-item lists used as filler comprehensiveness
  • inline_header_list - Restructure boldfaced inline-header vertical lists
  • unnecessary_table - Convert small tables to prose
  • regression_to_mean - Restore specific facts replaced by vague praise

6. Apply Safe Fixes

If --dry-run:

## Safe Fixes (would apply automatically)

| # | File | Line | Type | Action |
|---|------|------|------|--------|
| 1 | README.md | 3 | synthetic_opener | Delete "In today's rapidly evolving..." |
| 2 | src/auth.py | 15 | narrating_obvious | Delete "# Check if user exists" |
| 3 | README.md | 42 | ai_vocabulary_high | Replace "utilize" with "use" |
...

Otherwise, apply fixes grouped by file to minimize file I/O:

  1. Sort findings by file, then by line number (descending, to avoid offset drift)
  2. For each file, apply all safe fixes in reverse line order
  3. For git artifacts (git:commit:*, git:pr:*), skip — these can't be auto-fixed. Report them for manual attention.

7. Handle Needs Review Fixes

If --dry-run, list them:

## Needs Review Fixes (would prompt interactively)

| # | File | Line | Type | Original | Suggested |
|---|------|------|------|----------|-----------|
| 4 | README.md | 8 | promotional_language | "powerful, enterprise-grade solution" | "authentication library" |
...

Otherwise, for each fix, prompt interactively:

[README.md:8] Promotional language: "powerful, enterprise-grade solution"
Suggested: "authentication library"
(y)es / (n)o / (e)dit / (s)kip all:

Track user choices:

  • y - Apply this fix as suggested
  • n - Skip this fix
  • e - User provides custom replacement
  • s - Skip all remaining interactive fixes

8. Validate Results

For each modified markdown file, verify basic validity:

# Check for broken markdown (unclosed code blocks, broken links)
# Simple check: matching ``` pairs
grep -c '```' "$file" | awk '{print ($1 % 2 == 0) ? "OK" : "WARNING: odd number of code fences"}'

For modified source files, check syntax is still valid:

Python:

python3 -c "import ast; ast.parse(open('$file').read())"

TypeScript/JavaScript:

npx -y acorn --ecma2020 "$file" > /dev/null 2>&1

If validation fails for any file, revert that file:

git checkout -- "$file"
echo "Reverted $file due to validation failure"

9. Report Results

## Humanize Summary

### Applied Fixes
- [x] README.md:3 - Deleted synthetic opener
- [x] README.md:42 - Replaced "utilize" with "use"
- [x] src/auth.py:15 - Deleted obvious comment

### Interactive Fixes
- [x] README.md:8 - Rewrote promotional language (user approved)
- [ ] docs/guide.md:22 - Skipped by user

### Skipped (Git Artifacts)
- [ ] git:commit:abc1234 - Chat leak in commit message (amend manually)

### Validation
- README.md: OK
- src/auth.py: OK

### Diff Summary
git diff --stat

10. Cleanup

On successful completion (all validations pass):

rm .beagle/ai-writing-review.json

If any validation fails, keep the file and report:

Review file preserved at .beagle/ai-writing-review.json
Fix issues and re-run, or restore with: git stash pop

Core Principles

  1. Delete first, rewrite second. Most AI patterns are padding. Removing them improves the text.
  2. Use simple words. Replace "utilize" with "use", "facilitate" with "help", "implement" with "add".
  3. Keep sentences short. Break compound sentences. One idea per sentence.
  4. Preserve meaning. Never change what the text says, only how it says it.
  5. Match the register. Commit messages are terse. READMEs are conversational. API docs are precise. Read references/developer-voice.md for the full register guide.
  6. Don't overcorrect. A slightly formal sentence is fine. Only fix patterns that read as obviously AI-generated.
  7. Understand regression to the mean. LLMs produce the most statistically likely output. Specific, unusual facts get replaced with generic, positive descriptions. When humanizing, restore specificity — replace vague praise with concrete details.
  8. Score density, not individual words. AI vocabulary words co-occur. One or two may be coincidental; a cluster of 3+ is a strong AI tell.

Example

# Preview all fixes without applying
/beagle-docs:humanize-beagle --dry-run

# Fix only vocabulary issues
/beagle-docs:humanize-beagle --category vocabulary

# Full codebase scan and fix
/beagle-docs:humanize-beagle --all

# Preview filler fixes only
/beagle-docs:humanize-beagle --category filler --dry-run

Rules

  • Always load reference material before applying fixes (step 4)
  • Never modify files without a stash or clean working directory
  • Apply safe fixes in reverse line order to avoid offset drift
  • Never auto-fix git artifacts (commits, PRs) — report them for manual action
  • Validate every modified file before considering it done
  • Revert files that fail validation
  • Write JSON report before displaying summary
  • Clean up JSON report only on full success

平台分布

Codex

35.4%
按下载量换算38

Claude

28.8%
按下载量换算31

Cursor

18.65%
按下载量换算20

Gemini CLI

9.97%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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