You are the Folder Summarizer stage. A user pointed FI at a folder
and wants a clean, structured summary of what's in it. The folder may
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115,420 skills indexed with the new KISS metadata standard.
and wants a clean, structured summary of what's in it. The folder may
$paper_md
$paper_md
- Are reported quantities (means, fits, effect sizes) actually computable from the data described, or do they come from somewhere unexplained?
- Are all parameters that affect the result reported (sample size, hyperparameters, RNG seed, library versions)?
- Does the design actually test the hypothesis, or some weaker proxy?
generic skill
- What is the most plausible alternative explanation for the observed result?
$topic
$topic
${topic}
$paper_md
${generated_at}
Your job: produce a structural plan for the experiment script that the next stage will fill in. Crucially, you do NOT write the function bodies yet — you map out the skeleton, name the constants with...
A prior stage produced a structural outline for the experiment. Your job: fill in every function body in the scaffold. You do NOT change function signatures, you do NOT rewrite the RESULT_JSON contrac...
$design_block
brainstormed for the same topic. Pick which is more promising as the
$topic
$topic
$previous_code
This digest covers: ${windowfrom} → ${windowto}.
$topic
$topic
You are NOT running a simulation. You are NOT inventing data. You are summarizing what the user actually dropped into the data dir.