---
name: citation-check
description: Verify citations, claims, and numbers before answering.
---

# 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.

## Output Contract

- Pass 1 outputs a numbered claim list in the required format.
- Pass 2 outputs a verification report with status for every claim.
- If any claim is unverified, hallucinated, or misquoted, block final output until fixed.

---

## 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:

| Type            | Pattern                                                    | Example                                          |
| --------------- | ---------------------------------------------------------- | ------------------------------------------------ |
| **Statistic**   | Any number with unit/context (%, $, count, ratio, decimal) | "92.3% accuracy", "$4.7B market"                 |
| **Comparative** | X is [comparative] than Y                                  | "3x faster than baseline"                        |
| **Temporal**    | Time-bound assertion                                       | "In 2024, adoption reached..."                   |
| **Attribution** | Claim tied to source                                       | "According to WHO...", "Smith et al. found..."   |
| **Causal**      | X causes/leads to/results in Y                             | "This reduces latency by..."                     |
| **Existence**   | Asserts something exists/is true                           | "There are 500M users", "The model supports..."  |
| **Ranking**     | Position claims                                            | "largest", "first", "top 3"                      |
| **Quote**       | Direct quotation                                           | Any text in quotation marks attributed to source |

### DO NOT extract as claims:

| Type                              | Example                                            | Reason                          |
| --------------------------------- | -------------------------------------------------- | ------------------------------- |
| Definitions                       | "Machine learning is a subset of AI"               | Definitional, not factual claim |
| Opinions marked as such           | "We believe...", "In our view..."                  | Explicitly subjective           |
| Hypotheticals                     | "If adoption continues...", "Could potentially..." | Speculative                     |
| Questions                         | "What drives growth?"                              | Not an assertion                |
| Future predictions without source | "Will reach $10B by 2030"                          | Unless citing a forecast report |
| Methodology descriptions          | "We used PyTorch 2.0"                              | Process, not factual claim      |
| Acknowledgments                   | "Thanks to our collaborators"                      | Not verifiable                  |

### 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.**

| Rule                 | Source      | Claim       | Status            |
| -------------------- | ----------- | ----------- | ----------------- |
| Exact match required | 96.555%     | 96.555%     | ✓ Verified        |
| Any rounding = error | 96.555%     | 97%         | ✗ Numerical Error |
| Any rounding = error | 96.555%     | 96.6%       | ✗ Numerical Error |
| Truncation = error   | 96.555%     | 96.5%       | ✗ Numerical Error |
| Sig figs must match  | 0.834       | 0.83        | ✗ Numerical Error |
| Units must match     | 96.555%     | 0.96555     | ✗ Numerical Error |
| Direction matters    | +12% growth | +15% growth | ✗ Hallucination   |
| Order of magnitude   | $4.7B       | $47B        | ✗ Hallucination   |

### Numerical Error Output Format

```markdown
### 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

| Level              | Criteria                                                   | Use when                            |
| ------------------ | ---------------------------------------------------------- | ----------------------------------- |
| **exact**          | ≥95% word overlap OR identical number with identical units | Direct quote, exact statistic       |
| **paraphrase**     | Same fact, different words, no interpretation added        | Restated finding                    |
| **interpretation** | Inference drawn from source data                           | Calculated from source, synthesized |

**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:

| Rank | Source Type                   | Examples                                          |
| ---- | ----------------------------- | ------------------------------------------------- |
| 1    | Primary source                | Original study, official report, raw data         |
| 2    | Government/institutional      | WHO, CDC, World Bank, national statistics offices |
| 3    | Peer-reviewed publication     | Nature, Science, IEEE, ACM                        |
| 4    | Industry reports (named)      | Gartner, McKinsey, Statista (with methodology)    |
| 5    | Reputable news citing primary | NYT, Reuters citing original source               |
| 6    | Secondary compilations        | Wikipedia (check their sources)                   |

**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:

| Condition              | Sources Required                                    |
| ---------------------- | --------------------------------------------------- |
| Primary source found   | 1 (if authoritative: .gov, peer-reviewed, official) |
| Only secondary sources | ≥2 independent sources agreeing                     |
| Sources conflict       | Status = "Unverified", note the conflict            |

---

## Tie-Breaker Rules

When uncertain, apply these rules. No judgment calls.

| Situation                                 | Rule                                                         |
| ----------------------------------------- | ------------------------------------------------------------ |
| Missing date on claim                     | Assume refers to most recent year available; flag "needs date" |
| Conflicting sources                       | Use most recent authoritative source; cite both; note conflict |
| Source not found after all queries        | Status = "Unverified" (NOT "Hallucination")                  |
| Number differs due to currency conversion | Flag as "Needs clarification: currency/units"                |
| Same org, multiple reports                | Use most recent; cite with date                              |
| Claim uses "approximately" or "about"     | Still verify base number is in valid range (±10% of source)  |
| Source is paywalled                       | Note "Source behind paywall, unable to verify exact text"    |
| Source is in different language           | Translate and verify; note translation                       |

---

## 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

```markdown
| 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

| Check                                   | Issue Type                             |
| --------------------------------------- | -------------------------------------- |
| Y-axis starts at non-zero               | "Visual Distortion: axis manipulation" |
| 3D effects distort proportions          | "Visual Distortion: 3D exaggeration"   |
| Missing error bars when source has them | "Misleading: uncertainty omitted"      |
| Different time ranges than source       | "Misleading: cherry-picked timeframe"  |

---

## 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

```markdown
### 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)

```markdown
## 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)

```markdown
### ✓ 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

```markdown
### 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