protein-docking-configurator
Prepare input files for molecular docking software, automatically determine Grid Box center and size. Supports AutoDock Vina, AutoDock4, and other mainstream docking tools.
77
66%
Does it follow best practices?
Impact
99%
0.99xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Data analysis/protein-docking-configurator/SKILL.mdQuality
Discovery
67%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description demonstrates strong domain specificity with concrete actions and tool names, making it highly distinctive within its niche. However, it lacks explicit trigger guidance ('Use when...') which limits Claude's ability to know when to select it, and could benefit from additional natural language terms users might employ when requesting docking-related help.
Suggestions
Add a 'Use when...' clause with trigger scenarios like 'Use when the user needs to set up docking simulations, prepare ligand/receptor files, or configure AutoDock parameters'
Include additional natural trigger terms users might say: 'ligand docking', 'protein-ligand docking', 'PDBQT', 'receptor preparation', 'docking simulation'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Prepare input files', 'automatically determine Grid Box center and size', and names specific tools (AutoDock Vina, AutoDock4). These are concrete, domain-specific capabilities. | 3 / 3 |
Completeness | Clearly answers 'what' (prepare input files, determine Grid Box parameters, supports specific tools) but lacks an explicit 'Use when...' clause or equivalent trigger guidance for when Claude should select this skill. | 2 / 3 |
Trigger Term Quality | Includes relevant technical terms like 'molecular docking', 'Grid Box', 'AutoDock Vina', 'AutoDock4', but missing common user variations like 'ligand docking', 'protein-ligand', 'PDBQT files', or simpler terms users might say. | 2 / 3 |
Distinctiveness Conflict Risk | Highly specialized domain (molecular docking) with distinct tool names (AutoDock Vina, AutoDock4) makes this unlikely to conflict with other skills. Clear niche in computational chemistry/bioinformatics. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides solid, actionable guidance with executable code examples for both CLI and Python module usage. However, it's bloated with template sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status) that don't help Claude use the tool. The workflow could benefit from explicit validation steps to verify configuration file generation succeeded.
Suggestions
Remove boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status) that don't provide actionable guidance for using the docking configurator
Add validation steps showing how to verify the generated configuration files are correct (e.g., checking output file exists, validating Grid Box dimensions are reasonable)
Include a brief workflow showing the complete process: preprocess PDB → generate config → verify output → use in docking software
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with good code examples, but includes unnecessary sections like Risk Assessment, Security Checklist, Evaluation Criteria, and Lifecycle Status that add bulk without providing actionable guidance for using the skill. | 2 / 3 |
Actionability | Provides fully executable command-line examples and Python code that are copy-paste ready. Parameter tables are clear, and multiple concrete examples cover different use cases (active site residues, reference ligand, manual parameters). | 3 / 3 |
Workflow Clarity | The skill presents clear command options and examples, but lacks explicit validation steps or feedback loops. The Notes section mentions preprocessing steps but doesn't integrate them into a clear workflow with checkpoints for verifying successful configuration generation. | 2 / 3 |
Progressive Disclosure | Content is reasonably organized with clear sections, but everything is in one file including boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria) that could be omitted or referenced elsewhere. No references to external documentation for advanced topics. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- aipoch/medical-research-skills
- Commit
ca9aaa4
- Reviewed
Table of Contents
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