credibledata
Official@credibledata
credibledata provides Malloy semantic-model query construction, chart rendering, and data analysis verification skills for the Credible analytics platform over MCP.
Agent Skills by credibledata
Showing 9 vetted skills indexed across 1 GitHub repositories.
credibledatamalloy-analysis-pitfalls
Detects common Malloy query construction and result interpretation errors during data analysis.
credibledatacredible-analysis-overview
Explains Credible's published semantic model hierarchy and retrieval judgment for Malloy-based data analysis.
credibledatamalloy-phrase-detection
Constructs search targets for the get_context tool by classifying phrases into dimension, measure, view, and source types.
credibledatamalloy-gotchas-rendering
Documents common Malloy renderer annotation mistakes for charts, dashboards, and theming.
credibledatamalloy-charts
Selects and annotates Malloy chart renderers for query result visualization.
credibledatamalloy-patterns
Indexes Malloy documentation topics for lookup via the search_malloy_docs tool.
credibledatamalloy-analysis
Guides structured data analysis against Malloy semantic models over MCP tools.
credibledatamalloy-gotchas-queries
Documents common Malloy query and view mistakes with corrected syntax patterns.
credibledatamalloy-queries
Provides Malloy query syntax patterns, error fixes, and chart annotation rules for semantic model queries.
Frequently Asked Questions About credibledata
FAQPage SchemaWhat tasks can I accomplish with credibledata's skills?▼
You can answer data questions against Malloy semantic models via MCP: discover sources, dimensions, measures, and joins with get_context, build and run queries with execute_query, choose chart types, add renderer annotations, and verify results against a checklist of common analysis pitfalls.
Who should use these Malloy analysis skills?▼
Data analysts and engineers querying Credible's published semantic models who need structured guidance on Malloy syntax, query patterns, chart selection, and mistake prevention when building views, notebooks, or dashboards.
How do the skills fit into a query session?▼
Start with credible-analysis-overview to understand model organization, use malloy-phrase-detection to build get_context search targets, consult malloy-queries and malloy-patterns while writing queries, then check malloy-gotchas-queries and malloy-gotchas-rendering before delivering results.
What common Malloy mistakes do these skills prevent?▼
They cover aggregate filter misuse, joined field aliasing errors, method syntax issues, time truncation versus grouping confusion, chart constraint violations, tag syntax errors, scale rules, and sparkline and big_value misconfiguration.
What are the prerequisites for using these skills?▼
You need access to Credible's published semantic models and an MCP environment exposing the get_context, execute_query, and search_malloy_docs functions, since the skills provide reference guidance rather than standalone executables.