Agent skill

Claim Investigation

by jwynia in jwynia/agent-skills

Systematically investigate social media claims and viral content.

MITAuto-check passedResearch & Science

Install Claim Investigation

skills CLI
$ npx skills add jwynia/agent-skills --skill claim-investigation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jwynia/agent-skills claim-investigation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jwynia/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/general/research/verification/claim-investigation .claude/skills/claim-investigation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
claim-investigation
GitHub stars
170
Token cost
~3.5k tokens
SKILL.md length
1,568 words
Files
1
Skills in repo
111
Repo updated
First seen
Licence
MIT

At a glance

Systematically investigate social media claims and viral content.

  • Works in 7 steps: Claim Decomposition → Entity Resolution → Systematic Verification → …
  • Fact-checking complex claims
  • SKILL.md covers Core Principle, Phase 1: Claim Decomposition, Phase 2: Entity Resolution and Phase 3: Systematic Verification, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Claim Investigation is an agent skill from jwynia/agent-skills. Systematically investigate social media claims and viral content. Use when fact-checking complex claims, when decomposing multi-part assertions, or when investigating narratives that mix facts with interpretation.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Fact-checking and source verification. The licence is MIT.

When your agent uses it

  • Fact-checking complex claims
  • Decomposing multi-part assertions
  • Investigating narratives that mix facts with interpretation

Example prompts

  • “/claim-investigation”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Claim Decomposition
  2. Entity Resolution
  3. Systematic Verification
  4. Source Evaluation
  5. Narrative Pattern Recognition
  6. Synthesis and Reporting
  7. Meta-Analysis

What it can do on your machine

Read from SKILL.md and the folder at commit e02ec7e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Claim Investigation loads about 3.5k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 1,568 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jwynia/agent-skills at commit e02ec7e, republished under its MIT licence (© jwynia). 1,568 words, ~3,518 tokens.

Download SKILL.mdSave it as .claude/skills/claim-investigation/SKILL.md (or your agent's skills folder).
name
claim-investigation
description
Systematically investigate social media claims and viral content. Use when fact-checking complex claims, when decomposing multi-part assertions, or when investigating narratives that mix facts with interpretation.
license
MIT
metadata.author
jwynia
metadata.version
1.0
metadata.type
diagnostic
metadata.mode
evaluative
metadata.domain
research

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
Show full SKILL.md (622 more words)Show less
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

© jwynia, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/general/research/verification/claim-investigation of jwynia/agent-skills.

Open the folder on GitHubat commit e02ec7e

Compare with similar skills

Claim Investigation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Claim Investigation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Claim Investigation this skilljwynia/agent-skills170—~3.5kAutomated safety check: PassMIT
Perplexity Web Searchdavila7/claude-code-templates33k11 repos~3.5kAutomated safety check: NotesMIT
Citation Verification GuideGalaxy-Dawn/claude-scholar5.7k2 repos~1.9kAutomated safety check: PassMIT
Article Fact Checkerdigoal/blog8.6k—~939Automated safety check: PassGPL-2.0
Deep Research Agent TeamImbad0202/academic-research-skills51k—~13kAutomated safety check: PassCustom licence
Docs Grounding Verifiermicrosoft/apm4k—~1.9kAutomated safety check: PassMIT

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Questions about Claim Investigation

What does Claim Investigation do?

Systematically investigate social media claims and viral content. Claim Investigation is an agent skill from jwynia/agent-skills. Systematically investigate social media claims and viral content.

When should I use Claim Investigation?

Claim Investigation fits situations like: fact-checking complex claims; decomposing multi-part assertions; investigating narratives that mix facts with interpretation.

How do I install Claim Investigation in Claude Code?

Run `npx skills add jwynia/agent-skills --skill claim-investigation -a claude-code`. Or copy the skill folder (skills/general/research/verification/claim-investigation in jwynia/agent-skills) into .claude/skills/claim-investigation in your project. Claude Code loads it when a task matches its description.

How do I install Claim Investigation in Codex?

Run `npx skills add jwynia/agent-skills --skill claim-investigation -a codex`. Or copy the skill folder (skills/general/research/verification/claim-investigation in jwynia/agent-skills) into .agents/skills/claim-investigation in your project. Codex loads it when a task matches its description.

Can I use Claim Investigation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jwynia/agent-skills --skill claim-investigation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/claim-investigation, .gemini/skills/claim-investigation, .github/skills/claim-investigation and .opencode/skills/claim-investigation in your project.

What does Claim Investigation need to run?

SKILL.md names no scripts, command-line tools or credentials: Claim Investigation is instructions for the agent only.

Does Claim Investigation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Claim Investigation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Claim Investigation use?

Claim Investigation is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Claim Investigation use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Claim Investigation?

Skills that share tags, products or a category with Claim Investigation: Perplexity Web Search (davila7/claude-code-templates, 33k stars), Citation Verification Guide (Galaxy-Dawn/claude-scholar, 5.7k stars), Article Fact Checker (digoal/blog, 8.6k stars) and Deep Research Agent Team (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Claim Investigation?

jwynia (a GitHub user) maintains it in jwynia/agent-skills, which has 170 GitHub stars. The repository holds 111 skills in this directory. The repository was last updated on February 24, 2026.

Source: jwynia/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.