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serenakeyitan/open-exam-skills/citation-check

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version: "1.0.0" 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

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

Pass 2: Verification Only

Take Pass 1 output as fixed input
Verify each claim_id in sequential order
NO re-extraction allowed — work only with Pass 1 claims
Apply Status Decision Tree to each claim
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

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

All versions