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veroq_verify

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Fact-check any claim by returning a verdict (supported, contradicted, partially supported, or unverifiable) with confidence score, evidence chain from verified sources, and source reliability ratings.

Instructions

Fact-check any claim with full evidence chain, confidence breakdown, and source reliability scores.

WHEN TO USE: After any agent (including yourself) makes a factual claim about earnings, revenue, market movements, mergers, acquisitions, or any financial data. Also use proactively to verify assumptions before making recommendations. This is the TRUST tool — it proves claims with evidence.

RETURNS: • verdict: supported | contradicted | partially_supported | unverifiable • confidence: 0-1 with 4-factor breakdown (source_agreement, source_quality, recency, corroboration_depth) • evidence_chain: array of {source, snippet, url, position, reliability} — actual quotes from real sources • receipt: hashable verification proof (id, claim_hash, verdict_hash, sources_hash) • Checks 200+ verified sources first, falls back to live web search — NOTHING returns "unverifiable" for newsworthy claims

COST: 3 credits. Results cached 1 hour (corpus) or 15 min (web fallback).

EXAMPLES: "NVIDIA reported record Q4 2025 earnings" → SUPPORTED (85%) with Reuters, Bloomberg evidence "The Federal Reserve cut rates in March 2026" → CONTRADICTED (92%) — they held rates steady "Apple is partnering with OpenAI" → SUPPORTED with 5 source evidence chain

CONSTRAINTS: Claim must be 10-1000 characters. Be specific — include names, numbers, dates for best results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYesThe factual claim to verify (10-1000 chars). Be specific — 'NVIDIA beat Q4 earnings by 20%' not just 'NVIDIA did well'
contextNoCategory hint to narrow search: tech, markets, crypto, policy, health, energy
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate safe read (readOnlyHint) and external fetching (openWorldHint). Description adds cost (3 credits), cache durations, fallback to live web, and claim length constraints, providing full behavioral disclosure without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections (WHEN TO USE, RETURNS, COST, EXAMPLES, CONSTRAINTS). Only necessary sentences, no fluff, and front-loaded with key purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Complete description for a tool with no output schema: covers when to use, input constraints, return structure (verdict, confidence, evidence_chain, receipt), cost, caching, and examples. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage but description adds value: specifies claim length (10-1000 chars), encourages specificity, and explains 'context' as category hint. This goes beyond schema definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool is for fact-checking claims with evidence. It specifies verb 'verify', resource 'claim', and features like evidence chain and confidence breakdown, distinguishing it from numerous sibling data/analysis tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit 'WHEN TO USE' section advises using after any agent makes factual claims, especially about financial data, and proactively for assumptions. Provides clear context and alternatives (other veroq tools) are implicitly distinct.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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