The results-analysis lens: turn a finished results store into settled claims, mechanism evidence, and paper-grade figures — for any field running experiments to publish (ML, optimization, operations research, systems). Use when the runs are done and you are analyzing the results, or stress-testing an analysis. The one shift: analysis is NOT "compute a mean and see who is bigger" — it is audit, attribution, and the language of evidence. You audit before you read (a too-good number is a bug until proven otherwise); you prove WHY the method wins with mechanism probes; and you defend against the garden of forking paths, which the agent era amplifies because cheap experiments make cheating cheap. Triggers on "analyze the results", "read the main table / the ablation", "is this result significant / real / statistical test / effect size", "which is better", "make the figures / plots", "interpret these numbers / why does my method work", "the result looks too good", "review my results / write up".
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryScience & researchStars0
About this skill
The results-analysis lens: turn a finished results store into settled claims, mechanism evidence, and paper-grade figures — for any field running experiments to publish (ML, optimization, operations research, systems). Use when the runs are done and you are analyzing the results, or stress-testing an analysis. The one shift: analysis is NOT "compute a mean and see who is bigger" — it is audit, attribution, and the language of evidence. You audit before you read (a too-good number is a bug until proven otherwise); you prove WHY the method wins with mechanism probes; and you defend against the garden of forking paths, which the agent era amplifies because cheap experiments make cheating cheap. Triggers on "analyze the results", "read the main table / the ablation", "is this result significant / real / statistical test / effect size", "which is better", "make the figures / plots", "interpret these numbers / why does my method work", "the result looks too good", "review my results / write up".
Quick start
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The results-analysis lens: turn a finished results store into settled claims, mechanism evidence, and paper-grade figures — for any field running experiments to publish (ML, optimization, operations research, systems). Use when the runs are done and you are analyzing the results, or stress-testing an analysis. The one shift: analysis is NOT "compute a mean and see who is bigger" — it is audit, attribution, and the language of evidence. You audit before you read (a too-good number is a bug until proven otherwise); you prove WHY the method wins with mechanism probes; and you defend against the garden of forking paths, which the agent era amplifies because cheap experiments make cheating cheap. Triggers on "analyze the results", "read the main table / the ablation", "is this result significant / real / statistical test / effect size", "which is better", "make the figures / plots", "interpret these numbers / why does my method work", "the result looks too good", "review my results / write up".
About this listing
Category
Science & research
Reported license
Apache-2.0
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