validate-data
Validate Data Analysis
Validate an analysis before it is shared with stakeholders. Focus on whether the question, data, methodology, calculations, visuals, claims, caveats, and recommendations are trustworthy enough for the stated audience and decision. This skill is for analysis QA, not raw dataset profiling alone. When validation depends on dataset reliability checks such as freshness, grain, missingness, duplicates, join coverage, or source mismatches, use $analyze-data-quality as a companion.
Skill Configuration
User Context
Mandatory pre-answer gate: Invoke data-analytics:user-context in preflight mode by loading data-analytics:user-context and running its preflight script before answering, searching connectors, retrieving evidence, creating artifacts, or drafting output. Do not look for a callable MCP tool named data-analytics:user-context. Use the returned data_analytics_preflight envelope as the source of truth for saved context, source-category mapping, semantic-layer registry, onboarding/final-response obligations, and conditional guidance; use saved context and semantic layers as source-selection inputs, not as substitutes for workflow-time reads from connected or provided sources. Do not read or reinterpret raw plugin state files unless preflight fails, declares required content omitted, local shell access is unavailable, or the user explicitly asks for raw state inspection.
Workflow
-
Inventory the artifact and claims.
Identify the report, notebook, spreadsheet, SQL, dashboard, chart, pasted analysis, or recommendation being validated. Inspect source artifacts when a path, link, query, notebook, spreadsheet, or dashboard is referenced. Extract the main question, audience, decision, key claims, headline numbers, data sources, time windows, populations, filters, comparison baselines, and stated caveats. Verify that every metric or KPI requested by the user appears in the analysis or is explicitly marked unavailable, not applicable, or out of scope.
-
Validate the question, methodology, and assumptions.