Skill: cutthemustard/data-ground-truth (version 1.0.1)

--- name: data-ground-truth description: Before presenting numbers in reports or recommendations, verify facts and check values against industry baselines. version: 1.0.0 metadata: openclaw: emoji: "📊" homepage: https://agentutil.net always: false --- # data-ground-truth When presenting numbers, metrics, or statistics in reports, recommendations, or analysis — verify the facts and contextualize the figures against industry baselines. Combines verify (live fact-checking) with norm (statistical benchmarking). ## When to Activate Use this skill when: - Writing a report that cites specific metrics (revenue, churn, conversion rates) - A user shares their business numbers and asks "is this good?" - Comparing a metric to industry standards ("how does our 5% churn compare?") - Building a recommendation that depends on current market data - Presenting financial figures that may have changed since training - Analyzing a dataset and wanting to flag outliers against known baselines **Do NOT use for:** opinions, qualitative assessments, or metrics with no established baseline. ## Workflow ### Step 1: Classify the data point Determine whether each number is: - **A factual claim** (exchange rate, stock price, population) → route to **verify** - **A business/performance metric** (churn rate, NPS, response time) → route to **norm** - **Both** (e.g., "our conversion rate of 3.2% is above average") → check both ### Step 2: Verify factual claims For current facts (prices, rates, dates), use verify-claim. **MCP (preferred):** `verify_claim({ claim: "The USD to EUR exchange rate is 0.92" })` **HTTP:** ```bash curl -X POST https://verify.agentutil.net/v1/verify \ -H "Content-Type: application/json" \ -d '{"claim": "The USD to EUR exchange rate is 0.92"}' ``` Handle verdicts per the verify-claim decision tree (confirmed → use, stale → update, disputed → present both sides, false → correct). ### Step 3: Benchmark metrics against baselines For business metrics, check where the value falls on the distribution. **MCP (preferred):** `norm_check({ category: "saas:churn_rate_monthly", value: 5.2, unit: "%" })` **HTTP:** ```bash curl -X POST https://norm.agentutil.net/v1/check \ -H "Content-Type: application/json" \ -d '{"category": "saas:churn_rate_monthly", "value": 5.2, "unit": "%"}' ``` For multiple metrics at once: ```bash curl -X POST https://norm.agentutil.net/v1/batch \ -H "Content-Type: application/json" \ -d '{"items": [{"category": "saas:churn_rate_monthly", "value": 5.2}, {"category": "saas:nps_score", "value": 45}]}' ``` Optional: add `company_size` (startup/smb/mid_market/enterprise) and `region` for more specific baselines. ### Step 4: Present with context When reporting findings, combine verification and benchmarking: | Data type | How to present | |-----------|---------------| | Verified fact | "The current [metric] is [current_truth] (verified live, [freshness])." | | Benchmarked metric | "[Value] is at the [percentile]th percentile — [assessment] for [category]." | | Both | "At [current_truth] (verified), this is [percentile]th percentile vs. industry ([baseline source])." | | Anomalous metric | Flag clearly: "[Value] is [assessment] — [percentile]th percentile. The typical range is [p25]-[p75]." | Assessment values from norm: `very_low`, `low`, `normal`, `high`, `very_high`, `anomalous`. ### Available baseline categories 121 baselines across 14 domains. Browse with: ```bash curl https://norm.agentutil.net/v1/categories ``` Common categories: `saas:churn_rate_monthly`, `saas:nps_score`, `saas:ltv_cac_ratio`, `ecommerce:cart_abandonment_rate`, `infrastructure:api_latency_p99`, `infrastructure:uptime_percentage`. ## Data Handling This skill sends claims (natural language text) and metric values (category identifiers + numbers) to two external APIs. No documents, user data, or file contents are transmitted. ## Pricing - Verify: 25 free/day, then $0.004/query - Norm: free category listing, $0.002/check or $0.001/batch item - Full ground-truth check (verify + norm): ~$0.006 per data point All via x402 protocol (USDC on Base). No authentication required for free tiers. ## Privacy No personal data collected. Claims cached up to 1 hour (verify), metric checks are stateless (norm). Rate limiting uses IP hashing only.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)