Imported from serenakeyitan/citation-check-skill (SKILL.md). Install upstream with npx skills add serenakeyitan/citation-check-skill. Copyright stays with the author.

Citation & Hallucination Checker v2

Verification tool with vision + web search. Validates every claim against authoritative sources or provided documents. Works with content in any language.

Design principle: Deterministic verification. Same input → Same output.

Two Verification Modes

Mode 1: Search Verification (Default)

• Searches web for authoritative sources
• Validates citations actually exist
• Checks if cited sources say what's claimed
• Finds original data for statistics

Mode 2: Doc-Only Verification

• User provides source document(s)
• EVERYTHING must trace to those docs
• Flags anything that appears to come from external knowledge
• Trigger: "only use this document" / "verify against the PDF only" / "don't search the web"

Two-Pass Architecture

Critical: Always use two separate passes. Never interleave extraction and verification.

Pass 1: Extraction Only

1. Read entire document/slides/images
2. Extract ALL claims using the Claim Extraction Rules below
3. Output numbered list: [claim_id] | [claim_text] | [claim_type] | [location]
4. NO verification in this pass
5. Present extraction to user for confirmation before proceeding

Pass 2: Verification Only

1. Take Pass 1 output as fixed input
2. Verify each claim_id in sequential order
3. NO re-extraction allowed — work only with Pass 1 claims
4. Apply Status Decision Tree to each claim
5. Generate final report

This prevents "discovering new claims" mid-verification and ensures consistency.

Claim Extraction Rules (Exhaustive)

Extract ONLY these claim types. Apply rules strictly — no judgment calls.

EXTRACT as claims:

DO NOT extract as claims:

Extraction Output Format

[C01] | "Model achieves 96.555% accuracy on ImageNet" | Statistic | Slide 3, bullet 2
[C02] | "Outperforms GPT-4 by 12% on reasoning tasks" | Comparative | Slide 3, bullet 3
[C03] | "According to Chen et al. (2024), transformers scale linearly" | Attribution | Slide 5, para 1
[C04] | "Market size reached $4.7B in 2024" | Statistic + Temporal | Slide 7, chart title

Status Decision Tree

Apply this tree to EVERY claim. Follow exactly — no shortcuts.

START
│
├─ Is this a CITATION claim (references a paper/report/source)?
│   ├─ YES → Go to CITATION VALIDATION
│   └─ NO → Go to STATISTIC/FACT VALIDATION
│
│
CITATION VALIDATION
│
├─ Step 1: Does the cited source exist?
│   │   Run ALL mandatory search queries (see Search Templates)
│   │
│   ├─ NO → Status: "Citation Not Found"
│   │        Issue: "Cannot locate [citation] in any database"
│   │        STOP
│   │
│   └─ YES → Step 2: Does source contain the claimed topic?
│             │
│             ├─ NO → Status: "Misquoted"
│             │        Issue: "Source exists but does not discuss [topic]"
│             │        STOP
│             │
│             └─ YES → Step 3: Does source support the exact claim?
│                       │
│                       ├─ YES (exact match) → Status: "Verified"
│                       │                       Confidence: "exact"
│                       │
│                       ├─ YES (paraphrase, same meaning) → Status: "Verified"
│                       │                                   Confidence: "paraphrase"
│                       │
│                       ├─ PARTIALLY (missing context) → Status: "Misleading"
│                       │   Issue: "Claim omits critical context: [what's missing]"
│                       │
│                       └─ NO (contradicts) → Status: "Hallucination"
│                           Issue: "Source says [X], claim says [Y]"
│
│
STATISTIC/FACT VALIDATION
│
├─ Step 1: Can you find an authoritative source?
│   │   Run ALL mandatory search queries (see Search Templates)
│   │
│   ├─ NO (no source found) → Status: "Unverified"
│   │                          Issue: "No authoritative source found"
│   │                          STOP
│   │
│   └─ YES → Step 2: Do values match EXACTLY?
│             │
│             ├─ YES → Status: "Verified"
│             │         Confidence: "exact"
│             │         STOP
│             │
│             └─ NO → Status: "Numerical Error"
│                      Go to NUMERICAL ERROR DETAILS
│
│
NUMERICAL ERROR DETAILS (Academic Precision Mode)
│
├─ Record:
│   • Source value: [exact number from source]
│   • Claimed value: [number in document being checked]
│   • Deviation: [calculate exact difference]
│   • Source location: [page, table, section]
│
├─ Classification:
│   • ANY rounding → Numerical Error
│   • ANY truncation → Numerical Error  
│   • Significant figures mismatch → Numerical Error
│   • Unit mismatch → Numerical Error
│   • Wrong direction (e.g., increase vs decrease) → Hallucination
│
└─ Exception: If source ITSELF provides rounded figure
    • e.g., Source says "96.555% (approximately 97%)"
    • Then claiming "97%" → Verified (cite the approximation)

Numerical Precision Rules (Academic Standard)

Default mode: Strict academic precision. Exact numbers only.

Numerical Error Output Format

### Numerical Error: [Claim ID]

| Field | Value |
|-------|-------|
| Claim | "Model achieves 97% accuracy" |
| Location | Slide 4, bullet 2 |
| Source | Chen et al. (2024), Table 3, p.8 |
| Source value | 96.555% |
| Claimed value | 97% |
| Deviation | +0.445% (rounded up) |
| Status | Numerical Error |
| Fix | Replace with: "Model achieves 96.555% accuracy" |

Confidence Classification

Rule: When uncertain between levels, use the MORE CONSERVATIVE option and flag for review.

Mandatory Search Templates

Run ALL applicable templates. Do not stop after first result.

For Academic Citations

Query 1: "[first author last name] [year] [first 3 words of title]"
Query 2: "[full paper title]" site:semanticscholar.org OR site:arxiv.org
Query 3: "[first author] [year] [venue/journal name]"
Query 4: "doi:[DOI]" (if DOI provided)
Query 5: "arxiv:[arxiv_id]" (if arXiv ID provided)

For Statistics (Market size, usage numbers, etc.)

Query 1: "[exact number with unit] [topic] [year]"
Query 2: "[topic] [year] statistics report site:statista.com"
Query 3: "[topic] [year] report site:mckinsey.com OR site:gartner.com"
Query 4: "[topic] market size [year] site:gov OR site:edu"
Query 5: "[topic] [number] original source"

For Company/Product Claims

Query 1: "[company name] [claim topic] press release [year]"
Query 2: site:[company domain] [claim topic]
Query 3: "[company name] [metric] official announcement"
Query 4: "[company name] [claim] SEC filing" (for public companies)

For Health/Medical Claims

Query 1: "[claim topic] site:who.int OR site:cdc.gov OR site:nih.gov"
Query 2: "[claim] systematic review site:cochrane.org"
Query 3: "[claim] meta-analysis pubmed"

For Government/Policy Claims

Query 1: "[policy/law name] site:gov"
Query 2: "[statistic] official statistics [country]"
Query 3: "[claim] [agency name] report"

Source Authority Hierarchy

When multiple sources found, prefer in this order:

Rule: If only Rank 5-6 sources found, status = "Unverified" with note "Only secondary sources found"

Multi-Source Verification (Search Mode)

A claim achieves "Verified" status only if:

Tie-Breaker Rules

When uncertain, apply these rules. No judgment calls.

Visual Data Verification

For every chart, graph, table, or diagram:

Step 1: Extract Data Points

• Read ALL values from the visual
• Record: axis labels, units, scale, legend
• Note any visual distortions (truncated axes, 3D effects, etc.)

Step 2: Find Source

• Search mode: Run search templates for the data
• Doc-only mode: Locate in source document

Step 3: Compare Value-by-Value

| Visual Element | Extracted Value | Source Value | Status |
|----------------|-----------------|--------------|--------|
| Bar 1 (2022) | 45% | 45.0% | ✓ Verified |
| Bar 2 (2023) | 62% | 58.3% | ✗ Numerical Error |
| Bar 3 (2024) | 78% | Not in source | ✗ Hallucination |

Step 4: Check Visual Integrity

Doc-Only Mode Workflow

Trigger phrases:

• "only use this document"
• "don't search the web"
• "verify against the PDF only"
• "everything should be from the source"

Step 1: Index Source Document

Build complete index before any verification:

SOURCE INDEX
Document: [filename]
Pages: [count]

Page 1:
- Text: [summary of content]
- Statistics: [list all numbers with context]
- Tables: [Table 1: columns X, Y, Z]
- Figures: [Figure 1: shows X]

Page 2:
...

Step 2: Apply Two-Pass Architecture

Same as search mode, but verification uses ONLY the source index.

Step 3: Trace Each Claim

Claim: [C01] "Model achieves 92% accuracy"
Search index for: "92", "accuracy", "performance"
├─ Found: Section 4.2, p.8 — "Our model achieves 92.1% accuracy"
│   └─ Status: Numerical Error (92% vs 92.1%)
│
OR
│
├─ Not found in index
│   └─ Status: "Not in Source"
│       Issue: "This claim cannot be traced to the provided document"
│       Likely: External knowledge / hallucination

Step 4: Flag ALL External Knowledge

In doc-only mode, ANY claim not traceable to source = problem

### External Knowledge Detected

These claims are NOT in the provided document:

| Claim ID | Claim | Status | Issue |
|----------|-------|--------|-------|
| C07 | "This method is widely adopted in industry" | Not in Source | Appears to be from model training data |
| C12 | "Published in Nature 2024" | Not in Source | Publication venue not mentioned in source |

Output Format

Summary Block (Always First)

## Verification Report

**Mode:** [Search / Doc-Only]
**Document:** [filename or description]
**Generated:** [timestamp]

### Summary
| Metric | Count |
|--------|-------|
| Total claims extracted | X |
| Verified | Y |
| Numerical Error | Z |
| Unverified | A |
| Hallucination | B |
| Misleading | C |
| Not in Source (doc-only) | D |

**Overall Status:** [PASS: All verified / FAIL: Issues found]

Detailed Findings (Grouped by Status)

### ✓ Verified Claims (N)

| ID | Claim | Source | Location | Confidence |
|----|-------|--------|----------|------------|
| C01 | "92.1% accuracy" | Chen et al. 2024 | Table 3, p.8 | exact |

### ✗ Numerical Errors (N)

| ID | Claim | Source Value | Claimed Value | Deviation | Fix |
|----|-------|--------------|---------------|-----------|-----|
| C03 | "97% accuracy" | 96.555% | 97% | +0.445% | Use 96.555% |

### ✗ Hallucinations (N)

| ID | Claim | Issue | Source Says |
|----|-------|-------|-------------|
| C05 | "3x faster" | Contradicts source | Source: 2.1x faster |

### ⚠ Unverified (N)

| ID | Claim | Issue |
|----|-------|-------|
| C08 | "$50B market" | No authoritative source found |

### ⚠ Misleading (N)

| ID | Claim | Issue | Missing Context |
|----|-------|-------|-----------------|
| C10 | "Best performance" | Cherry-picked metric | Only on subset; overall performance lower |

Sources Consulted

### Sources

| ID | Citation | Type | URL | Used For |
|----|----------|------|-----|----------|
| S1 | Chen et al. (2024) | arxiv | https://arxiv.org/... | C01, C02, C03 |
| S2 | Statista Market Report | report | https://statista.com/... | C08 |

Critical Rules

1. Two-pass always — Extract first, verify second. Never interleave.
2. Every claim gets checked — No exceptions, no skipping "obvious" ones.
3. Exact numbers only — 96.555% ≠ 97% in academic mode.
4. Find the origin — Don't accept secondary sources citing unknown primaries.
5. Run ALL search templates — Don't stop after first result.
6. Citations must be real — Search to confirm papers/reports exist.
7. Check what sources actually say — A real paper can still be misquoted.
8. In doc-only mode, flag ALL external knowledge — Even if it's true.
9. When uncertain, be conservative — "Unverified" is safer than false "Verified".
10. Follow tie-breaker rules — No ad-hoc judgment calls.

Language Support

• Accepts content in any language
• Searches in the appropriate language for sources
• Reports in the same language as user's request
• Cross-language verification supported (e.g., Chinese slides citing English papers)
• When translating for verification, note: "Translated from [language]"

Output Format Options

Quick: Summary + critical issues only (Numerical Errors, Hallucinations, Unverified) Full: Complete traceability report with all claims JSON: Machine-readable audit (see references/citation_schema.json)

Changelog

v2.0 — Consistency update

• Added Two-Pass Architecture (extract → verify separation)
• Added exhaustive Claim Extraction Rules
• Added Status Decision Tree (deterministic classification)
• Added strict Numerical Precision Rules (academic mode)
• Added Mandatory Search Templates
• Added Multi-Source Verification requirements
• Added Tie-Breaker Rules for edge cases
• Added Confidence Classification thresholds