Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/paramjani21-diffdock
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About
Use cases: productivity
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/diffdock
What's inside
- Skill name
diffdock- Description
- Run or plan DiffDock molecular docking workflows. Use when a task asks for protein-ligand pose prediction, docking setup, ligand/protein preparation, pose ranking, or docking-result verification.
- License
- MIT
- Instructions
- 15 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# DiffDock Use this skill for protein-ligand docking and pose review. Workflow: 1. Record protein source, chain selection, binding site context, ligand identity, protonation/tautomer assumptions, and known cofactors. 2. Verify the available execution path and dependency stack before claiming a docking run is possible. 3. Preserve input PDB/mmCIF, ligand SDF/SMILES, prepared structures, command, seed, package version, and logs. 4. Save ranked poses, confidence scores, contact summaries, and 3D previews as Feynman artifacts. 5. Compare poses against known ligands, active-site residues, experimental structures, or orthogonal docking where the conclusion matters. Report docking as a ranked hypothesis, not binding proof.
From ParamJani21/feynman, MIT.
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compute-env-setup
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Set up a reproducible Feynman compute environment for research jobs.
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Configure Feynman specialists, skills, connectors, permissions, memory categories, compute providers, and project setup.
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Predict quick protein structures with ESMFold-style workflows.
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Use Evo2-style biological sequence models for generation, scoring, or variant-effect analysis.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jul 5, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/ParamJani21/feynman
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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boltz
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Run or plan Boltz biomolecular structure predictions for proteins, complexes, ligands, or nucleic-acid assemblies.
SkillCFreshness: CClaude Code +9 - 0.469score
borzoi
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Use Borzoi-style regulatory genomics models for sequence-to-expression or variant-effect analysis.
SkillCFreshness: CClaude Code +9 - 0.469score
chai1
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Run or prepare Chai-1 structure predictions for biomolecular complexes.
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compute-env-setup
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Set up a reproducible Feynman compute environment for research jobs.
SkillCFreshness: CClaude Code +9 - 0.469score
customize
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Configure Feynman specialists, skills, connectors, permissions, memory categories, compute providers, and project setup.
SkillCFreshness: CClaude Code +9 - 0.469score
alphafold2
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Predict or audit protein structures with AlphaFold2-style workflows.
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Cite this page
diffdock skill. Agent Mart. https://agentmart.dev/skills/paramjani21-diffdock (last updated 2026-10-24)