Use when you have an approved research question and need a concrete analysis plan, before touching outcome data or fitting any model
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Use after framing a question and before designing an analysis, or when choosing a method, judging whether a result is novel, or needing a prior effect size for a power calculation
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See how to installReview the instructions the agent will receive before you install.
Before designing an analysis, ground the question and your chosen methods in what is already known. Most questions have established methods, known confounds, and prior effect sizes. Reinventing a method badly — or rediscovering a known artifact and reporting it as a finding — wastes effort and erodes credibility.
Core principle: Find out what is already known before you generate new claims.
This is the science analog of reading the existing codebase before writing new code. It is a flexible skill — adapt depth to the stakes of the investigation.
framing-research-questions, before designing-the-analysisSurvey four things:
science-superpowers:dispatching-parallel-investigations for the workflow. This keeps your own context clean.After grounding, invoke science-superpowers:designing-the-analysis. Bring forward the adopted methods, the confound list, and the prior effect size for powering the design.
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Use when you have an approved research question and need a concrete analysis plan, before touching outcome data or fitting any model
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Use when facing 2+ independent investigations that can proceed without shared state - parallel literature survey, multi-dataset replication, or pre-specified robustness checks
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Use when your human partner has explicitly opted into exploratory or feasibility mode - a compute-heavy simulation, an unproven pipeline, an unbenchmarked solver, an untested cluster job - or when whether the work can run at all is still unknown, when a plan's largest configuration has never been executed, when a memory or wall-clock ceiling is estimated rather than measured, or when someone proposes pre-registering over runs that have never happened
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Use when you have a pre-registered analysis plan to execute inline in this session with review checkpoints, on a platform without subagents
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You MUST use this before any data analysis or investigation - before exploring a dataset, loading or profiling data, running a model, computing a statistic, or testing an idea, and before any outcome data is touched
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Use when a result is surprising, impossible, contradicts a sanity check, a pipeline fails, a model won't converge, or a replication fails - before adjusting anything
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