Run an overnight autonomous B-vs-C parallel insight-discovery workflow that surfaces ah-ha findings from data for a client. Use when: (1) a client wants interesting or surprising insights (not just monitoring or action items); (2) you want to hedge LLM creativity against deterministic rigor by running two tracks in parallel and consolidating; (3) the work fits an 8-hour autonomous window with review-panel gates; (4) the underlying data supports both exploratory querying and mechanical candidate scans. Specializes overnight-review-client-delivery for INSIGHT DISCOVERY rather than deliverable polishing — the two are sister skills with different problem shapes. ALWAYS use this skill when the user asks for "ah-ha insights", "surprise patterns", "funnel leaks", "hidden findings", "overnight analysis to surface X", or wants a dual-approach (creative + mechanical) for client-facing insight work — even if they don't explicitly name the pattern. NOT for: synchronous analysis (use exploratory- data-analysis), single-track LLM exploration (use deep-research), or work that needs user input mid-stream.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryScience & researchStars0
About this skill
Run an overnight autonomous B-vs-C parallel insight-discovery workflow that surfaces ah-ha findings from data for a client. Use when: (1) a client wants interesting or surprising insights (not just monitoring or action items); (2) you want to hedge LLM creativity against deterministic rigor by running two tracks in parallel and consolidating; (3) the work fits an 8-hour autonomous window with review-panel gates; (4) the underlying data supports both exploratory querying and mechanical candidate scans. Specializes overnight-review-client-delivery for INSIGHT DISCOVERY rather than deliverable polishing — the two are sister skills with different problem shapes. ALWAYS use this skill when the user asks for "ah-ha insights", "surprise patterns", "funnel leaks", "hidden findings", "overnight analysis to surface X", or wants a dual-approach (creative + mechanical) for client-facing insight work — even if they don't explicitly name the pattern. NOT for: synchronous analysis (use exploratory- data-analysis), single-track LLM exploration (use deep-research), or work that needs user input mid-stream.
Quick start
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Run an overnight autonomous B-vs-C parallel insight-discovery workflow that surfaces ah-ha findings from data for a client. Use when: (1) a client wants interesting or surprising insights (not just monitoring or action items); (2) you want to hedge LLM creativity against deterministic rigor by running two tracks in parallel and consolidating; (3) the work fits an 8-hour autonomous window with review-panel gates; (4) the underlying data supports both exploratory querying and mechanical candidate scans. Specializes `overnight-review-client-delivery` for INSIGHT DISCOVERY rather than deliverable polishing — the two are sister skills with different problem shapes. ALWAYS use this skill when the user asks for "ah-ha insights", "surprise patterns", "funnel leaks", "hidden findings", "overnight analysis to surface X", or wants a dual-approach (creative + mechanical) for client-facing insight work — even if they don't explicitly name the pattern. NOT for: synchronous analysis (use exploratory- data-analysis), single-track LLM exploration (use deep-research), or work that needs user input mid-stream.
About this listing
Category
Science & research
Reported license
MIT
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI