Fact Check — Primary Source Claim Verification

Verify factual claims against primary sources using web lookups. Training data recall is NOT evidence.

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When to Use

• Backlog items marked UNVERIFIED
• Plugin documentation with uncited claims about tools, APIs, CLI flags
• Skills that reference specific software behavior without citation
• After code review agents flag potential fabrication

When NOT to Use

• Structural findings (broken links, missing files, malformed YAML) — those are filesystem checks, not fact checks
• Code logic bugs — use /dh:root-cause-tracing-process instead
• Research on new tools — use /research-curator instead

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Evidence Rules

<evidence_rules>

Adapted from the root-cause-tracing-process evidence chain protocol.

Valid evidence (one of these MUST support each verdict):

1. WebFetch output — content retrieved from an official documentation URL
2. WebSearch result — search results linking to authoritative sources
3. Command output — npx <tool> --help, gh api, or similar CLI output
4. Repository source code — file content from the tool's GitHub repo via gh or clone
5. MCP tool output — mcp__Ref, mcp__exa results with URLs

NOT valid evidence (these MUST NOT support verdicts):

• Training data recall ("I know this from my training")
• Inference from absence ("the docs don't mention it, so it doesn't exist")
• Reasoning from analogy ("tool X works this way, so tool Y does too")
• Documentation that describes intent without observed behavior
• Another AI's claim without primary source backing

</evidence_rules>

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Claim Extraction

Parse the input to extract discrete, falsifiable claims:

flowchart TD
    Start([Parse input]) --> Q{Input type?}
    Q -->|Backlog item title| ReadBacklog[Run backlog list --format json, find matching item]
    Q -->|Plugin path| ScanFiles[Scan SKILL.md and references for factual claims]
    Q -->|--all-unverified| FindAll[Run backlog list --format json, filter UNVERIFIED items]
    ReadBacklog --> Extract[Extract falsifiable claims]
    ScanFiles --> Extract
    FindAll --> Extract
    Extract --> Classify[Classify each claim]
    Classify --> Spawn[Spawn verification agents]

Claim Classification

For each claim, determine:

1. Claim text — the specific assertion
2. Primary source — where to check (official docs URL, GitHub repo, CLI help)
3. Verification method — WebFetch URL, run CLI command, search GitHub issues
4. Falsifiability — what would disprove this claim?

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Verification Agent Spawning

Spawn @fact-checker agents in parallel waves of 5.

Each agent receives:

CLAIM: {exact claim text}
SOURCE_FILE: {file containing the claim, with line numbers}
PRIMARY_SOURCE: {URL or command to check against}
VERIFICATION_METHOD: {WebFetch | WebSearch | CLI command | gh API}
FALSIFICATION_CRITERIA: {what would disprove this}

Wave Execution

flowchart TD
    Start([Claims extracted]) --> Count{How many claims?}
    Count -->|1-5| Wave1[Wave 1 — all in parallel]
    Count -->|6-10| Split2[Wave 1 — first 5, Wave 2 — remaining]
    Count -->|11+| SplitN[Waves of 5, sequential]
    Wave1 --> Collect[Collect verdicts]
    Split2 --> SeqWaves[Execute waves sequentially]
    SeqWaves --> Collect
    SplitN --> SeqWaves
    Collect --> Report[Generate report]

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Verdict Format

Each agent returns a structured verdict:

CLAIM: {the claim being checked}
VERDICT: VERIFIED | REFUTED | INCONCLUSIVE
EVIDENCE:
  - Source: {URL or command}
  - Retrieved: {date}
  - Content: {relevant excerpt from primary source}
EXPLANATION: {how the evidence supports the verdict}
CITATION: {formatted citation for backlog/docs update}

Verdict Criteria

• VERIFIED — primary source confirms the claim. Evidence excerpt matches.
• REFUTED — primary source contradicts the claim. Evidence excerpt shows the discrepancy.
• INCONCLUSIVE — primary source could not be reached, does not address the claim, or is ambiguous. State what additional step would resolve it.

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Chain of Verification (CoVe) Requirement

Each agent MUST apply CoVe before finalizing:

1. Initial lookup — fetch primary source, form initial verdict
2. Verification questions — generate 2-3 questions that could falsify the initial verdict
3. Independent check — answer each verification question using a different source or method
4. Final verdict — confirm or revise based on cross-checking

This prevents the agent from confirming its own bias in a single lookup.

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Report Format

After all waves complete:

# Fact Check Report

**Date**: {YYYY-MM-DD}
**Scope**: {backlog item title | plugin path | all-unverified}
**Claims checked**: {N}

## Summary

| Verdict | Count |
|---------|-------|
| VERIFIED | {N} |
| REFUTED | {N} |
| INCONCLUSIVE | {N} |

## Verdicts

### Claim 1: {claim text}

**Verdict**: {VERIFIED|REFUTED|INCONCLUSIVE}
**Source**: {primary source URL}
**Evidence**: {excerpt}
**Citation**: {formatted citation}

### Claim 2: ...

## Backlog Updates

{For each REFUTED or VERIFIED claim, the specific edit to make to the per-item file}

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Post-Actions

1. Update backlog — for VERIFIED/REFUTED claims, update the backlog item's Status field in the per-item file
2. Lint — uv run prek run --files .claude/backlog/
3. Commit — git add .claude/backlog/ && git commit -m "docs(backlog): fact-check {N} claims ({date})"

For INCONCLUSIVE claims, add a note to the backlog item describing what additional verification is needed.

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References

• Evidence chain protocol adapted from root-cause-tracing-process
• Wave spawning pattern from research-curator
• Anti-hallucination checkpoint from skill-research-process
• Chain of Verification from cove-prompt-design