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.
4k tokens
context cost
the whole folder, loaded on every use
1
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instructions only
0
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how many repositories repackaged it
128
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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:
There is a House Leader (entity exists)
There was an AZ-07 special election (event occurred)
Someone won that election (result exists)
The winner has not been seated (current state)
A refusal action occurred (specific action claim)
Causal relationship with Epstein files (causation claim)
1.2 Classify Each Component
| Type | Description | Verifiability |
|------|-------------|---------------|
| ENTITY | Person, organization, place | Usually verifiable |
| EVENT | Something that allegedly happened | Often verifiable |
| STATE | Current condition or status | Usually verifiable |
| PROCESS | Official procedure or mechanism | Verifiable |
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
| Task | Agent Type | When to Spawn |
|------|------------|---------------|
| Source research | general-purpose | When tracing claim origins |
| Timeline construction | general-purpose | When 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)
| Skill | What it provides |
|-------|------------------|
| research | Initial source discovery and query expansion |
| media-meta-analysis | Understanding of source biases and media patterns |
Outbound (this skill enables)
| Skill | What this provides |
|-------|-------------|
| fact-check | Verified facts for post-generation checking |
| sensitivity-check | Context for evaluating representation claims |
Complementary
| Skill | Relationship |
|-------|--------------|
| research | Use research for broad information gathering, claim-investigation for specific claim verification |
| fact-check | Use claim-investigation for external claims, fact-check for AI-generated content verification |
How to use it
Copy the folder
Take jwynia/claim-investigation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
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