experiment-design-planner
Experiment Design Planner
Turn a research claim into an experiment plan that can actually answer it. This skill is for planning before running, not for reporting completed results.
Use this skill when:
- a user is about to run a new experiment or ablation
- a paper claim needs evidence
- baselines, metrics, controls, or datasets are unclear
- the user is changing too many variables at once
- cluster/compute time should not be wasted on ambiguous runs
- reviewer-proof evidence is needed before submission
Pair this skill with:
research-project-memorywhen the experiment plan should become project-level evidence, risk, and action memoryrun-experimentafter the design is ready to executeexperiment-report-writerafter results existpaper-reviewer-simulatorto stress-test whether the evidence will satisfy reviewers
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Initialize an ML research project control root. Use for paper/code/slides repos, shared memory, GitHub Project alignment, agent guidance, worktree policy, and lifecycle handoffs.
39init-python-project
Initialize or enhance a Python/ML project. Use for new repos or forks needing production structure, uv environment setup, and research evidence docs.
37new-workspace
Create Git branches or worktrees for research code and paper versions. Use for experiments, baselines, rebuttal fixes, arXiv/camera-ready branches, and worktree memory.
36project-sync
Sync verified code-side experiment results into paper memory. Use when logs, reports, run docs, or user-confirmed metrics should become paper-facing evidence.
36init-latex-project
Initialize a LaTeX academic paper project. Use for new conference or journal papers needing templates, macros, venue preambles, and writing guidance.
36add-git-tag
Create annotated Git milestone tags. Use when completing a phase, releasing a version, or marking a research checkpoint.
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