skills/md-analyze/SKILL.md
Molecular dynamics trajectory analysis using MDClaw CLI tools. Routes concat, metric, and troubleshooting workflows through focused guidance pages.
npx skillsauth add matsunagalab/mdclaw md-analyzeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Read skills/common/preamble.md, skills/common/tool-output.md,
skills/common/node-cli-patterns.md, and skills/common/run-loop.md before
acting. Use mdclaw plan_next --job-dir <job_dir> to confirm the job is ready
for analysis and to get the leaf prod parent.
Analysis is always user-initiated. Production does not chain into analysis;
the user or harness invokes this skill when ready. In harnesses with slash
commands, /md-analyze is the shortcut.
If the job belongs to a study with study_plan.json, use the plan's analysis
list as the starting point for metric selection. Treat it as scientific intent,
not as a brittle execution contract: missing or incomplete plan fields should
not block normal analysis.
skills/md-analyze/concat.mdskills/md-analyze/metrics.mdskills/md-analyze/troubleshooting.mdskills/md-analyze/analysis.mdConfirm these fields before running analysis:
| Parameter | Value |
|-----------|-------|
| Target | job directory |
| Analysis data scope | segment, production_chain, or comparison |
| Analysis subjects | optional for segment/production_chain; required for comparison |
| Comparison mapping | required for different chains/topologies; initial types: residue_number, atom_selection |
| Validation | require analysis_data_scope; comparison is binary/pairwise with two unique subject labels |
| Leaf prod node | requested node or deepest continuation leaf |
| Atom selection | mdtraj selection, default "protein" |
| Stride | integer, default 1 |
For comparison analyses, create the node with explicit subjects and mapping:
Use two completed production_chain analyze nodes as parents.
Put analysis_subjects and comparison_mapping on the comparison node itself,
not on the parent production_chain analyze nodes.
The resolver still exposes multi-parent analyze inputs as branches_input for
tool compatibility.
For residue_number mappings, each reference uses
subject_label:residue_id; the residue_id is a string, not a number.
For atom_selection mappings, selection values are mdtraj selection strings.
mdclaw create_node --job-dir <job_dir> --node-type analyze \
--parent-node-ids <analyze_apo> <analyze_holo> \
--label "apo_vs_holo" \
--conditions '{"analysis_data_scope": "comparison",
"analysis_subjects": [
{"label": "apo"},
{"label": "holo"}
],
"comparison_mapping": {
"type": "residue_number",
"pairs": [["apo:10", "holo:10"]]
}}'
Create an analyze node first, then run analysis tools with both --job-dir
and --node-id.
The structure-preview and visual-review procedure is shared across all stages.
Follow skills/common/visual-qa.md when the user wants a structural snapshot or
a completed prod/analyze artifact would benefit from a quick obvious-accident
check.
development
Generate monomer conformational source candidates with BioEmu, then hand them to MDClaw preparation.
testing
Study-level planning for MDClaw. Turns scientific questions into a small MD research plan, planned jobs, analysis intent, and decision criteria before handing off to stage skills.
data-ai
Run MDPrepBench and MDStudyBench tasks with prompt-driven MD agents and deterministic scorer commands. Use for benchmark runs, agent submissions, and comparing MD agents.
data-ai
AI-driven protein structure prediction using Boltz-2 for single proteins, multimers, and protein-ligand complexes.