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hum-source-criticism嗡嗡声源批评

Agent Skill

hum-source-criticism 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。

总安装

399

周安装

16

GitHub Stars

125

下载量

129
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:hum-source-criticism(嗡嗡声源批评)
来源仓库:https://github.com/asgard-ai-platform/skills
仓库路径:skills/hum-source-criticism
安装命令:
npx skills add https://github.com/asgard-ai-platform/skills --skill hum-source-criticism
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/asgard-ai-platform/skills --skill hum-source-criticism

简介

hum-source-criticism 用于查找、检索和筛选相关信息,支持基于关键词快速定位结果。

  • 适用于源材料分析和信息筛选场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需确认权限范围。
  • 使用前建议核实是否会触发联网或文件读写操作。
  • 可结合原始 README 继续核验具体功能和使用限制。

SKILL.md

Source Criticism

Overview

Source criticism is a systematic method for evaluating whether information is trustworthy. Originally from historical methodology, it's now essential for navigating an information environment flooded with misinformation, opinion-as-fact, and AI-generated content.

Framework

IRON LAW: No Source Is Automatically Trustworthy

Every source — including academic journals, government data, and news from
reputable outlets — has potential biases, errors, and limitations. Credibility
is assessed, not assumed. "It's from the New York Times / 中央社" is not
sufficient — WHAT are they reporting, based on WHAT evidence, and do other
sources corroborate it?

Source Classification

Primary sources: Direct evidence from the time/event (original documents, raw data, eyewitness accounts, original research, official records)

Secondary sources: Analysis or interpretation of primary sources (textbooks, review articles, news analysis, biographies)

Tertiary sources: Compilations of primary and secondary (encyclopedias, Wikipedia, databases) — starting points, not endpoints

Four Tests of Source Credibility

1. External Criticism — Is the source authentic?

  • Who created it? Are they who they claim to be?
  • When was it created? Is the date consistent?
  • Is it the original or has it been altered?
  • Is the publication/platform reputable?

2. Internal Criticism — Is the content reliable?

  • Does the author have expertise in this topic?
  • What is the author's potential bias or interest?
  • Is the evidence cited? Can it be verified?
  • Is the reasoning logical? Are conclusions supported by the evidence?

3. Triangulation — Do multiple independent sources agree?

  • Check 3+ independent sources (not copies of the same original report)
  • "Independent" means different authors, different organizations, different methods
  • Agreement across independent sources strengthens confidence

4. Currency — Is the information current enough?

  • When was it published? Has the situation changed since then?
  • For fast-moving topics (AI, policy, markets), even 6-month-old sources may be outdated

Red Flags for Misinformation

Red FlagDescription
No author or organization identifiedWho stands behind this claim?
Emotional language without evidenceDesigned to provoke, not inform
No primary sources citedClaims without traceable evidence
"Studies show" without naming the studyVague appeals to authority
Single source amplified across many sitesSame claim copied, not independently verified
Too good to be true / too outrageousExtreme claims require extreme evidence
URL/domain mimics reputable sourceFakecnn.com, bbc-news.co (not bbc.co.uk)

Output Format

# Source Evaluation: {Source/Claim}

## Source Identity
- Author/Organization: {who}
- Publication: {where}
- Date: {when}
- Type: Primary / Secondary / Tertiary

## Credibility Assessment
| Test | Assessment | Evidence |
|------|-----------|---------|
| External (authentic?) | ✓/⚠/✗ | {reasoning} |
| Internal (reliable?) | ✓/⚠/✗ | {reasoning} |
| Triangulation (corroborated?) | ✓/⚠/✗ | {other sources checked} |
| Currency (current?) | ✓/⚠/✗ | {relevance of date} |

## Red Flags
- {any detected red flags}

## Verdict
- Credibility: High / Moderate / Low
- Recommended action: {trust / verify further / discard}

Examples

Correct Application

Scenario: Evaluating a viral social media post claiming "Taiwan's GDP will surpass South Korea's by 2027"

TestAssessmentEvidence
ExternalAnonymous account, no institutional affiliation, chart has no data source
InternalUses nominal GDP (not PPP), cherry-picks semiconductor sector projection, ignores exchange rate volatility
TriangulationIMF and World Bank projections show no such convergence; no reputable analyst makes this claim
CurrencyPosted this month

Red flags: Emotional headline ("Taiwan DESTROYS Korea"), no primary data source cited, single unsourced chart Verdict: Low credibility — discard ✓

Incorrect Application

  • "This is from Reuters, so it must be true" → Credibility assumed, not assessed. Even reputable sources can be wrong, outdated, or framing an issue in a particular way. Violates Iron Law.

Gotchas

  • Bias ≠ unreliable: Every source has a perspective. A labor union's report on working conditions is biased but may contain accurate data. Assess bias AND accuracy separately.
  • Wikipedia is a starting point: It's a tertiary source with references. Follow the references to primary/secondary sources. Don't cite Wikipedia as evidence — cite what Wikipedia cites.
  • AI-generated content: AI can produce convincing but fabricated "sources" (fake papers, fake quotes, fake statistics). Verify that cited sources actually exist.
  • Consensus ≠ truth, but it's a strong signal: Scientific consensus (climate change, vaccine safety) is the strongest available evidence. Lone dissenting "experts" who contradict consensus need extraordinary evidence.
  • Source credibility is domain-specific: A cardiologist is a credible source on heart disease but not on economics. Match expertise to the claim.

References

  • For CRAAP test (Currency, Relevance, Authority, Accuracy, Purpose), see references/craap-test.md
  • For fact-checking tools and databases, see references/fact-check-tools.md

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平台分布

Codex

35%
按下载量换算45

Claude

30.77%
按下载量换算40

Cursor

17.29%
按下载量换算22

Gemini CLI

9.58%
按下载量换算12

安全审计

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Snyk

可疑

权限和风险

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