Fact-Check Skill Systematic verification of claims in generated content. Designed to catch hallucinations, confabulations, and unsupported assertions. Why Separate Passes Matter The Fundamental Problem: LLMs generate plausible-sounding content by predicting what should come next. This same mechanism produces hallucinations—confident statements that feel true but aren't. An LLM in generation mode cannot reliably catch its own hallucinations because: Attention is on generation , not verification Coherence pressure makes false claims feel correct in context Same weights that produced the error will confirm it No external grounding to contradict the confabulation The Solution: Verification must be a separate cognitive pass with: Fresh attention focused solely on each claim Explicit source checking (not memory/training data) Adversarial stance toward the content External grounding where possible Diagnostic States F1: No Verification Pass Symptoms: Content generated and delivered without any fact-checking. Risk: Hallucinations pass through undetected. Intervention: Run verification pass before delivery. Extract claims, check each against sources. F2: Self-Verification (Invalid) Symptoms: Same pass asked to "check your facts" while generating. Risk: False confidence—errors confirmed by same process that created them. Intervention: Complete generation first, then run separate verification pass with explicit source requirements. F3: Memory-Based Verification (Unreliable) Symptoms: Claims checked against "what I know" without external sources. Risk: Hallucinations verified by hallucinated knowledge. Intervention: Require explicit source citation for each verified claim. If no source available, mark as unverified. F4: Selective Verification Symptoms: Only some claims checked; others assumed correct. Risk: Unchecked claims may contain errors. Intervention: Systematic extraction of ALL verifiable claims. Check each, or explicitly mark unchecked items. F5: Verification Complete Symptoms: All claims extracted, each checked against sources, confidence levels assigned. Indicators: Source citations present, unverified claims marked, confidence explicit. The Verification Process Phase 1: Claim Extraction Extract every verifiable statement from the content. Claim types to extract: Factual assertions ("X is Y", "X causes Y") Statistics and numbers ("40% of...", "in 2023...") Attributions ("According to X...", "Research shows...") Definitions ("X means...", "X is defined as...") Historical claims ("X happened in...", "X was founded by...") Causal claims ("X leads to Y", "X prevents Y") Comparative claims ("X is better than Y", "X is the largest...") What to skip: Opinions clearly marked as such Hypotheticals and speculation (if labeled) Logical deductions from stated premises Direct quotes (verify attribution, not content) Phase 2: Claim Categorization Categorize each claim by verifiability: Category Description Verification Strategy Verifiable-Hard Numbers, dates, names, quotes Must match source exactly Verifiable-Soft General facts, processes, mechanisms Source should substantially support Attribution "X said...", "According to..." Verify source exists and said something similar Inference Conclusions drawn from evidence Verify premises, assess reasoning Opinion-as-Fact Subjective claim stated as objective Flag for rewording or qualification Phase 3: Source Verification For each claim, attempt verification:
Claim Verification Log
Claim 1: "[exact claim text]"
** Category: ** [Verifiable-Hard/Soft/Attribution/Inference] - ** Source checked: ** [specific source] - ** Finding: ** [Confirmed/Partially supported/Not found/Contradicted] - ** Confidence: ** [High/Medium/Low] - ** Notes: ** [discrepancies, qualifications needed]
Claim 2: ... Verification outcomes: Outcome Meaning Action Confirmed Source explicitly supports claim Keep, cite source Partially supported Source supports part, not all Qualify or narrow claim Not found No source located Mark unverified, consider removing Contradicted Source says opposite Remove or correct Outdated Source is dated; current state may differ Update or add recency caveat Phase 4: Confidence Assignment Assign overall confidence to the content: Level Criteria High All key claims verified; no contradictions found Medium Most claims verified; some unverified but plausible Low Significant claims unverified; some corrections needed Unreliable Multiple contradictions found; major revision needed Hallucination Patterns Common hallucination types to watch for: 1. Plausible Fabrication Pattern: Specific details that sound right but don't exist. Examples: Fake paper citations, non-existent statistics, invented quotes. Detection: Verify specific claims against primary sources. 2. Confident Extrapolation Pattern: Reasonable inference stated as established fact. Examples: "Studies show..." (no specific study), "Experts agree..." (no citation). Detection: Require specific source for any claim of external support. 3. Temporal Confusion Pattern: Mixing information from different time periods. Examples: Old statistics presented as current, defunct organizations described as active. Detection: Check dates on sources, verify current status. 4. Attribution Drift Pattern: Correct information attributed to wrong source. Examples: Quote assigned to wrong person, finding attributed to wrong study. Detection: Verify attribution specifically, not just content. 5. Amalgamation Pattern: Combining details from multiple sources into one fictional source. Examples: Invented study that combines real findings from separate papers. Detection: Verify the specific source exists and contains all attributed claims. 6. Precision Inflation Pattern: Adding false precision to vague knowledge. Examples: "Approximately 47.3%" when only "about half" is supported. Detection: Check if source actually provides that level of precision. Verification Checklist Before releasing fact-checked content: Claims extracted? All verifiable statements identified Sources checked? Each claim verified against external source Specific, not memory? Verification used actual sources, not LLM training data Contradictions flagged? Conflicts between claims and sources noted Unverified marked? Claims without sources explicitly identified Confidence stated? Overall reliability level communicated Separate pass? Verification done after generation, not during Integration with Research Skill Research Phase Fact-Check Role During research Verify claims in sources themselves After synthesis Verify that synthesis accurately represents sources Before delivery Final pass to catch hallucinations in output Handoff pattern: Research skill gathers and synthesizes information Content is generated based on research Fact-check skill runs as separate pass Corrections made, confidence assigned Output delivered with verification status Operational Constraints What This Skill Cannot Do Verify during generation — Must be separate pass Catch all hallucinations — Some may slip through Verify without sources — No sources = unverified, not "verified by knowledge" Replace domain expertise — Can check sources exist, not evaluate quality When Verification Is Most Critical Context Verification Level Published content Full verification required Decision support Key claims must be verified Educational content High accuracy expected Casual conversation Light verification acceptable Creative fiction N/A (different standards) Anti-Patterns Pattern Problem Fix "I'm confident" Confidence ≠ accuracy Require source citation "To the best of my knowledge" Memory is unreliable Check external source "Generally speaking" Vagueness hides uncertainty Be specific or mark unverified "Research shows" Which research? Cite specific source Verify-while-generating Same pass can't catch own errors Separate passes mandatory Check one, assume rest Partial verification Check all or mark unchecked Output Format When delivering fact-checked content:
[Content Title] [Content body with claims]
Verification Status ** Overall Confidence: ** [High/Medium/Low] ** Verified Claims: ** - [Claim 1] — Source: [citation] - [Claim 2] — Source: [citation] ** Unverified Claims: ** - [Claim 3] — No source found; treat as uncertain ** Corrections Made: ** - [Original claim] → [Corrected claim] (Source: [citation]) ** Caveats: ** - [Any limitations or qualifications] Output Persistence This skill writes primary output to files so work persists across sessions. Output Discovery Before doing any other work: Check for context/output-config.md in the project If found, look for this skill's entry If not found or no entry for this skill, ask the user first : "Where should I save output from this fact-check session?" Suggest: explorations/fact-check/ or a sensible location for this project Store the user's preference: In context/output-config.md if context network exists In .fact-check-output.md at project root otherwise Primary Output For this skill, persist: Claims extracted - all verifiable statements identified Verification results - each claim with source and status Confidence assessment - overall content reliability Corrections made - any changes from original Conversation vs. File Goes to File Stays in Conversation Verification status report Discussion of sources Claim-by-claim results Clarifying questions Confidence assessment Verification process Corrections and caveats Real-time feedback File Naming Pattern: {content-name}-factcheck-{date}.md Example: research-synthesis-factcheck-2025-01-15.md Source Framework This skill extends the research cluster with post-generation verification. Distinct from research (which gathers information) and operates as quality control on output. Related: skills/research/SKILL.md (pre-generation), references/doppelganger/ (truth hierarchies)