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Agent Skill · 研究检索

claim-investigation(索赔调查)

claim-investigation 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。

claim-investigation 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,权限为只读;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 18,846。

总安装 5,880周安装 250GitHub Stars 67下载 2,060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
MIT

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:claim-investigation(索赔调查)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/claim-investigation
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill claim-investigation
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill claim-investigation

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。

系统性拆解社交媒体等来源的声明,区分事实与解读。将复杂主张分解为原子级可验证单元并独立核查真伪。明确标注哪些信息可证实、哪些属于推测或无法确认范畴。适用于新闻核实、舆情分析或争议性观点溯源场景。claim-investigation 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/claim-investigation

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/jwynia/agent-skills --skill claim-investigatio…;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

claim-investigation 怎么安装?

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

claim-investigation 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。

claim-investigation 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

claim-investigation 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

claim-investigation 用的人多吗?

公开数据是累计安装 5,880 次,近一周安装 250 次,下载 2,060 次,GitHub 67 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。

claim-investigation 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 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
claim-investigation

索赔调查 · 本页

5,88067只读MIT有提醒

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

Claim Investigation: Systematic Fact-Checking Skill

You help systematically investigate claims from social media and other sources, separating verifiable facts from narrative interpretation and identifying what can and cannot be confirmed.

Core Principle

Complex claims typically combine verifiable facts with unverifiable interpretations. Effective investigation decomposes claims into atomic components, verifies each independently, and clearly distinguishes between confirmed facts and narrative framing.

Phase 1: Claim Decomposition

1.1 Extract Atomic Claims

Break the statement into individual verifiable claims. Each should be:

  • A single factual assertion
  • Independently verifiable
  • Free of narrative interpretation

Example Decomposition: Original: "The House Leader refusing to seat the newly-elected AZ-07 special election winner because she'd vote to release the Epstein files"

Atomic claims:

  1. There is a House Leader (entity exists)
  2. There was an AZ-07 special election (event occurred)
  3. Someone won that election (result exists)
  4. The winner has not been seated (current state)
  5. A refusal action occurred (specific action claim)
  6. Causal relationship with Epstein files (causation claim)

1.2 Classify Each Component

TypeDescriptionVerifiability
ENTITYPerson, organization, placeUsually verifiable
EVENTSomething that allegedly happenedOften verifiable
STATECurrent condition or statusUsually verifiable
PROCESSOfficial procedure or mechanismVerifiable
CAUSATIONClaimed reason or motivationRarely verifiable
NARRATIVEInterpretive framingNot directly verifiable

1.3 Identify Missing Information

Note what's conspicuously absent:

  • Unnamed entities ("the winner" instead of a name)
  • Unspecified dates
  • Missing procedural context
  • Absent opposing perspectives

Phase 2: Entity Resolution

2.1 Resolve Vague References

Convert vague references to specific, searchable terms:

  • "House Leader" → Current House Speaker/Majority Leader name
  • "newly-elected winner" → Candidate names from election results
  • "Epstein files" → Specific documents/investigations

2.2 Establish Timeline

For each event:

  • When did it allegedly occur?
  • What is normal timeline for this type of event?
  • Are there procedural deadlines involved?

2.3 Identify Key Actors

  • Primary actors (those taking alleged actions)
  • Secondary actors (those affected)
  • Official bodies with relevant authority
  • Potential sources of verification

Phase 3: Systematic Verification

3.1 Verify Foundational Facts First

Start with most basic, verifiable claims:

  1. Did the event occur?
  2. Do the entities exist?
  3. Are basic facts correct?

Search Strategy:

  • Official sources first (.gov, electoral bodies)
  • Cross-reference multiple news sources
  • Look for primary documents

3.2 Investigate Procedural Context

For any claimed action/inaction:

  1. What is normal procedure?
  2. What are requirements?
  3. What is typical timeline?
  4. What are legitimate reasons for delays?

3.3 Examine Causation Claims

For any "because" or causal claim:

Direct Evidence:

  • Quoted statements from alleged actor
  • Official statements or press releases
  • Video/audio of relevant statements

Indirect Evidence:

  • Other explanations for observed facts
  • Standard reasons for similar situations
  • Procedural explanations

Context:

  • Previous positions by involved parties
  • Historical precedents
  • Timeline compatibility

Phase 4: Source Evaluation

4.1 Source Priority Order

  1. Official government records/databases
  2. Direct statements from involved parties
  3. Court documents or legal filings
  4. Contemporary news reports (multiple outlets)
  5. Analysis or opinion pieces (noted as such)

4.2 Credibility Markers

For each source, note:

  • Type (official, news, advocacy, social media)
  • Date relative to events
  • Whether claims are attributed
  • Presence of supporting documentation
  • Corrections or updates issued

4.3 Bias Indicators

Document without dismissing:

  • Source's typical political alignment
  • Stakeholder relationships
  • Pattern of coverage
  • Language choices (neutral vs charged)

Phase 5: Narrative Pattern Recognition

5.1 Identify Narrative Constructions

Patterns indicating narrative rather than fact:

  • Causal chains without evidence ("X because Y because Z")
  • Mind-reading claims ("thinks that," "wants to")
  • Selective fact inclusion
  • Temporal conflation (mixing time periods)
  • False dichotomies

5.2 Find Counter-Narratives

For each narrative:

  • What facts support it?
  • What facts complicate it?
  • What alternative narratives explain same facts?
  • What facts are excluded?

5.3 Missing Context

What would change interpretation:

  • Standard procedures being followed
  • Similar historical cases
  • Full quotes vs partial quotes
  • Events immediately before/after

Phase 6: Synthesis and Reporting

6.1 Report Structure

VERIFIED FACTS:
- [Fact] (Source: [citation])

DISPUTED/UNCLEAR:
- [Claim]:
  - Supporting: [source]
  - Contradicting: [source]
  - Unable to verify: [what's missing]

CONTEXT NEEDED:
- [Procedural context]
- [Historical precedent]
- [Timeline considerations]

NARRATIVE ELEMENTS:
- [Claim]
  - Facts that support: [list]
  - Facts that complicate: [list]
  - Alternative explanations: [list]

6.2 Confidence Levels

LevelMeaning
CertainMultiple primary sources confirm
ProbableMultiple credible sources align, no contradictions
PossibleSome evidence supports, gaps remain
UnclearContradictory evidence or insufficient info
FalseContradicted by authoritative sources

Phase 7: Meta-Analysis

7.1 Information Gaps

Document what couldn't be determined:

  • Information that should exist but wasn't found
  • Questions that remain unanswered
  • Time constraints on verification

7.2 Manipulation Indicators

Patterns suggesting intentional misrepresentation:

  • Key facts consistently omitted
  • Misquoted or out-of-context statements
  • Conflation of different events/people
  • Old events presented as new

7.3 Further Investigation

If initial investigation reveals deeper issues:

  • What additional tools/access would help?
  • What questions should be asked of officials?
  • What documents should be requested?

Search Query Construction

  • Start broad, then narrow
  • Use multiple phrasings for same concept
  • Include date ranges when relevant
  • Search for both supporting and contradicting evidence
  • Use exact phrases for quotes, broad terms for concepts

Output Principles

  1. Lead with verified facts
  2. Clearly separate facts from analysis
  3. Include all relevant context
  4. Present multiple valid interpretations where applicable
  5. Never assert causation without evidence
  6. Acknowledge investigation limitations

Output Persistence

Output Discovery

  1. Check for context/output-config.md in the project
  2. If found, look for this skill's entry
  3. If not found, ask user: "Where should I save investigation reports?"
  4. Suggest: research/investigations/ or explorations/research/

Primary Output

  • Decomposed claims - Atomic components with classifications
  • Verification results - Confidence levels per component
  • Context documentation - Procedural and historical context
  • Synthesis report - Using standard report structure

File Naming

Pattern: {topic}-investigation-{date}.md

Verification (Oracle)

What This Skill Can Verify

  • Decomposition complete - All atomic claims identified? (High confidence)
  • Entity resolution - Vague references resolved? (High confidence)
  • Source evaluation - Credibility markers documented? (High confidence)

What Requires Human Judgment

  • Source reliability - Contextual trust assessment
  • Narrative interpretation - Which framing is most accurate?
  • Manipulation detection - Intent behind information gaps

Oracle Limitations

  • Cannot assess motivations behind claims
  • Cannot predict how information will evolve

Feedback Loop

Session Persistence

  • Output location: See context/output-config.md
  • What to save: Decomposition, verification, context, synthesis
  • Naming pattern: {topic}-investigation-{date}.md

Cross-Session Learning

  • Check for prior investigations on related topics
  • Build on previous source evaluations
  • Failed verifications inform methodology

Design Constraints

This Skill Assumes

  • A specific claim to investigate (not general research)
  • Verifiable components exist within the claim
  • Sources are accessible for verification

This Skill Does Not Handle

  • General research - Route to: research
  • AI output verification - Route to: fact-check
  • Media pattern analysis - Route to: media-meta-analysis

Degradation Signals

  • Single-source verification (confirmation rush)
  • Accepting causation without evidence
  • Dismissing entire claims for single errors

Reasoning Requirements

Standard Reasoning

  • Single claim decomposition
  • Basic entity resolution
  • Simple source evaluation

Extended Reasoning (ultrathink)

  • Multi-claim investigation - [Why: claims interact and context builds]
  • Narrative analysis - [Why: detecting manipulation patterns]
  • Deep source tracing - [Why: finding original sources through citation chains]

Trigger phrases: "full investigation", "trace all sources", "analyze the narrative"

Execution Strategy

Sequential (Default)

  • Decomposition before verification
  • Foundational facts before causation claims
  • Individual components before synthesis

Parallelizable

  • Verifying independent atomic claims
  • Researching multiple sources simultaneously

Subagent Candidates

TaskAgent TypeWhen to Spawn
Source researchgeneral-purposeWhen tracing claim origins
Timeline constructiongeneral-purposeWhen mapping event sequences

Context Management

Approximate Token Footprint

  • Skill base: ~3.5k tokens (phases + templates)
  • With examples: ~4.5k tokens
  • With full output structure: ~5k tokens

Context Optimization

  • Focus on current investigation phase
  • Report structure is reference, not in-context
  • Examples optional

When Context Gets Tight

  • Prioritize: Current phase, active claims
  • Defer: Full template structure, all phases
  • Drop: Meta-analysis section, search examples

Anti-Patterns

1. Confirmation Rush

Pattern: Finding one source that matches the claim and declaring it verified. Why it fails: Single-source verification misses errors, biases, and coordinated misinformation where multiple outlets repeat the same false claim without independent verification. Fix: Require at least 2-3 independent sources. Trace claims back to primary sources. Check if "multiple sources" are actually just repeating the same original source.

2. Causation Collapse

Pattern: Accepting "X happened because Y" claims when only "X happened" and "Y exists" are verified. Why it fails: Correlation proves co-occurrence, not causation. Human pattern-matching fills in causal links that may not exist. Political narratives especially exploit this gap. Fix: Demand direct evidence for causation (stated intent, documented decisions). When causation can't be verified, report it as "alleged motivation" or "claimed reason."

3. Premature Debunking

Pattern: Finding one fact wrong and dismissing the entire claim without investigating other components. Why it fails: Complex claims often mix true and false elements. Dismissing everything because one part is wrong misses real issues embedded in the narrative. Fix: Decompose fully, verify each component independently. Report accuracy per-component: "Claims A and C are verified; claim B is false; claim D is unverifiable."

4. Authority Fallacy

Pattern: Accepting official sources uncritically because they're "authoritative." Why it fails: Official sources can be wrong, incomplete, outdated, or deliberately misleading. Authority reduces probability of error but doesn't eliminate it. Fix: Cross-reference official sources with other evidence. Note when official sources have incentives to misrepresent. Distinguish between "official position" and "verified fact."

5. Narrative Anchoring

Pattern: Starting with a hypothesis about what's "really happening" and investigating to prove it. Why it fails: Confirmation bias shapes what evidence you seek and how you interpret it. You'll find "evidence" for any narrative if you look hard enough. Fix: Start with the specific claims made. Investigate each on its own terms. Actively seek disconfirming evidence. Document alternative explanations that fit the same facts.

Integration

Inbound (feeds into this skill)

SkillWhat it provides
researchInitial source discovery and query expansion
media-meta-analysisUnderstanding of source biases and media patterns

Outbound (this skill enables)

SkillWhat this provides
fact-checkVerified facts for post-generation checking
sensitivity-checkContext for evaluating representation claims

Complementary

SkillRelationship
researchUse research for broad information gathering, claim-investigation for specific claim verification
fact-checkUse claim-investigation for external claims, fact-check for AI-generated content verification

平台分布

Claude Code

28.32%
按下载量换算583

OpenCode

20.55%
按下载量换算423

Gemini CLI

19.36%
按下载量换算399

Antigravity

12.49%
按下载量换算257

Codex

7.98%
按下载量换算164

windsurf

3.57%
按下载量换算74

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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