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 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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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Load the pre-registered plan, review it critically, execute all steps exactly as registered, report when complete.
Announce at start: "I'm using the executing-analysis skill to run this analysis."
Note: Tell your human partner that Science Superpowers works much better with access to subagents — the protocol-compliance and rigor reviews catch more when run by fresh agents. If subagents are available, use science-superpowers:subagent-driven-analysis instead.
The plan MUST be pre-registered and frozen (science-superpowers:preregistering-analysis) and the workspace set up (science-superpowers:setting-up-reproducible-analysis). If either is missing, stop and do it first. Executing before freezing turns the analysis exploratory.
For each step:
science-superpowers:verifying-results-before-claiming before marking done.After each natural group of steps (e.g., data prep, then primary model), pause and report results to your human partner before continuing. Keep confirmatory and exploratory results clearly separated in every report.
After all steps complete and verified:
science-superpowers:requesting-red-team-review on the whole result.science-superpowers:reporting-and-archiving-findings.STOP immediately when:
science-superpowers:investigating-anomalous-results (do NOT quietly drop data or tweak parameters)Ask rather than guess. A guess that changes the analysis silently destroys the result's credibility.
Required workflow skills:
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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
中文简介正在准备中。当前显示原文说明。
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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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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Use before running any confirmatory analysis or looking at outcome data, when testing a hypothesis, computing a p-value, or about to claim an effect - locks predictions and decision rules before results are seen
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