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name: verifier description: Trust and evidence verification engine for claims, sources, screenshots, profiles, offers, and suspicious messages. Use whenever the user asks whether something is true, credible, safe, trustworthy, manipulated, misleading, or worth believing. Evaluates evidence quality, source reliability, internal consistency, and obvious red flags. Produces a clear verdict, confidence level, risk notes, missing evidence, and a recommended next verification step. Local-only storage.

Verifier: Trust the evidence, not the vibe.

Core Philosophy

1. Verify claims, not feelings.
2. Distinguish evidence from presentation.
3. Confidence should reflect proof quality, not tone or certainty.
4. When proof is weak, say what is missing.

Runtime Requirements

• Python 3 must be available as python3
• No external packages required

Agent vs Script Responsibilities

• The LLM must extract text from screenshots, summarize external links, and convert outside content into structured evidence before passing it into verifier scripts.
• Verifier scripts do not browse the web, inspect images directly, or fetch remote content.
• Verifier scripts score only the claim and evidence that have already been provided.

Storage

All data is stored locally only under:

• ~/.openclaw/workspace/memory/verifier/cases.json

No external sync. No cloud storage. No third-party APIs.

Case Types

• claim: A statement that needs verification
• source: A source whose credibility needs assessment
• screenshot: An image or claimed visual proof
• profile: A person or identity claim
• offer: A proposal, deal, or opportunity
• message: A suspicious or questionable message
• website: A site or page that needs trust evaluation

Evidence Schema

Each evidence item should be structured with:

• id
• type
• content
• support_level (supports, contradicts, neutral)
• source_label
• added_at

Core Outputs

Each verification case should aim to produce:

• a verdict
• a confidence level
• risk notes
• missing evidence
• a recommended next step

Key Workflows

• Capture a case: add_case.py --title "..." --type claim --claim "..."
• Score a case: score_case.py --id VER-XXXX
• Review a case: show_case.py --id VER-XXXX
• Update evidence: update_case.py --id VER-XXXX --notes "..."
• Close a case: close_case.py --id VER-XXXX --verdict inconclusive
• List open cases: list_cases.py

Scripts

Script	Purpose
add_case.py	Capture a new verification case
score_case.py	Score credibility, risk, and evidence quality
show_case.py	Show one case in detail
list_cases.py	List stored cases
update_case.py	Update notes, status, and evidence
close_case.py	Close a case with final verdict
init_storage.py	Initialize local storage