crispr-grna-designer
Design CRISPR gRNA sequences for specific gene exons with off-target prediction and efficiency scoring. Trigger when user needs gRNA design, CRISPR guide RNA selection, or genome editing target analysis.
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill crispr-grna-designer88
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
100%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 is a well-crafted skill description that excels across all dimensions. It provides specific capabilities (gRNA design, off-target prediction, efficiency scoring), includes natural domain-specific trigger terms, explicitly states both what the skill does and when to use it, and occupies a clear niche that won't conflict with other skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Design CRISPR gRNA sequences', 'off-target prediction', 'efficiency scoring', and specifies the target as 'specific gene exons'. Uses third person voice correctly. | 3 / 3 |
Completeness | Clearly answers both what ('Design CRISPR gRNA sequences for specific gene exons with off-target prediction and efficiency scoring') and when ('Trigger when user needs gRNA design, CRISPR guide RNA selection, or genome editing target analysis'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'gRNA design', 'CRISPR', 'guide RNA selection', 'genome editing', 'target analysis'. These cover the domain terminology biologists would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly specialized niche in CRISPR/genome editing with distinct technical triggers like 'gRNA', 'CRISPR', 'guide RNA'. Unlikely to conflict with other skills due to the specific domain terminology. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides comprehensive, actionable guidance for CRISPR gRNA design with excellent parameter documentation and concrete usage examples. However, it suffers from bloat in meta-documentation sections (security checklists, lifecycle status, evaluation criteria) that don't help Claude perform the task. The workflow could be strengthened with explicit validation checkpoints given the high-risk nature of the task.
Suggestions
Remove or significantly condense the Risk Assessment, Security Checklist, Evaluation Criteria, and Lifecycle Status sections - these are project management artifacts, not actionable skill content
Add an explicit numbered workflow that integrates the validation warning: 1. Design guides → 2. Review off-target counts → 3. Filter by efficiency threshold → 4. Select top 3-5 for experimental validation
Move the Technical Notes warning about 60-80% correlation earlier and integrate it into the workflow as a mandatory checkpoint before proceeding
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains substantial useful information but includes sections that add bulk without proportional value (Risk Assessment table, Security Checklist, Evaluation Criteria, Lifecycle Status). These meta-sections are more appropriate for project documentation than a skill file teaching Claude how to perform a task. | 2 / 3 |
Actionability | Provides concrete, executable bash commands for basic, high-specificity, and batch processing use cases. Includes specific function names, parameter tables with defaults, and a complete JSON output schema that is copy-paste ready. | 3 / 3 |
Workflow Clarity | While individual commands are clear, the skill lacks an explicit step-by-step workflow with validation checkpoints. For a HIGH difficulty task requiring experimental validation, there should be clearer sequencing (e.g., 1. Design → 2. Validate computationally → 3. Review off-targets → 4. Select top candidates). The warning about manual verification is present but not integrated into a workflow. | 2 / 3 |
Progressive Disclosure | Well-structured with clear sections and appropriate references to external files (references/, scoring_algorithms.pdf, scripts/main.py). Content is organized logically from use cases through parameters, output format, examples, and technical details. References are one level deep and clearly signaled. | 3 / 3 |
Total | 10 / 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 | |
- Reviewed
Table of Contents
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