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Search and analyze electron microscopy data — cryo-EM density maps (EMDB), fitted atomic models (PDB), raw micrograph datasets (EMPIAR), and cryo-electron tomography volumes (CryoET Data Portal).
Passed 10 of 16 test cases with the skill, and 12 of 16 without it.
and 1 more in the full report
4 fixed12 passed either way3 still failing6 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
When assessing two candidate atomic models built into a 3.0 Angstrom density map, Model Alpha has a cross-correlation coefficient of 0.75 and Model Beta has a cross-correlation coefficient of 0.45. Which model meets standard validation criteria for satisfactory map fit?
| Checked | Without skill | With skill |
|---|---|---|
| Selects Model Alpha based on its 0.75 cross-correlation coefficient. | Passed | Passed |
| Identifies a cross-correlation threshold of 0.7 or greater as indicating a reasonable fit. | Missed | Passed |
The instructions your model reads when the skill loads.
Pipeline for discovering and analyzing electron microscopy data across the full resolution spectrum: from 3D density maps (EMDB) to fitted atomic models (PDB), raw micrograph datasets (EMPIAR), and cryo-electron tomography volumes (CryoET Data Portal). Connects EM data to structural biology context via PDB and AlphaFold.
Guiding principles:
EM resolution determines what you can see. TEM resolves individual protein complexes (~2nm). Cryo-EM achieves near-atomic resolution (<4Å) for large complexes. SEM shows surface topology. Choose the right EM modality for the question.
When uncertain about any scientific fact, SEARCH databases first rather than reasoning from memory. A database-verified answer is always more reliable than a guess.
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
Typical triggers:
Not this skill: For X-ray crystallography or NMR structures, use PDB search tools directly. For protein structure prediction, use tooluniverse-protein-structure.
| Database | Content | Best For |
test cases passed, vs 12 / 16 without
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