Query live connected sources via Coral MCP to produce evidence-based answers.
npx skills add https://github.com/withcoral/skills --skill coral-withcoral
Please help me install this Agent Skill. Skill: coral Source: https://github.com/withcoral/skills/tree/main/coral Command: npx skills add https://github.com/withcoral/skills --skill coral-withcoral
It reduces guessing and stale information by letting you query the connected world (GitHub, Jira, Slack, Linear, Datadog, Sentry, files, and other live sources) before answering or changing anything.
Use Coral MCP to query live connected sources and cite the resulting evidence for your answer instead of relying on assumptions.
High-intent search queries and answers about installing and using this skill.
Querying live data from GitHub, Jira, and Slack requires discovering the right catalogs and table metadata via Coral MCP, then executing bounded SQL queries with appropriate LIMIT clauses and correct identifier quoting to return evidence-based answers.
Discovering available table metadata and required filters requires using Coral MCP catalog search and list functions to inspect columns and table functions, ensuring you construct safe, accurate SQL queries grounded in the specific source schema.
Yes, you can use SQL to inspect real-time ticket activity across Linear and Sentry by discovering the appropriate catalog objects through Coral MCP and executing narrowly-scoped queries that apply the required source-specific filters.
Handling empty results versus missing MCP availability requires operational guardrails that clearly separate configuration or credential blockers from empty-result scenarios, ensuring you only query accessible and properly configured connected systems.
Limitations of querying file-backed data and Datadog through live SQL include the need to keep exploration bounded to avoid noisy metadata dumps, requiring specific table functions and correct identifier quoting to ensure safe query execution.
Yes, inspecting coral.columns and coral.table_functions is required before running bounded SQL queries to identify the necessary filters, virtual columns, and call examples needed to construct accurate and safe data retrieval operations.
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