Expert system for generating comprehensive biomedical phenotype introductions with structured academic content. Use when users request detailed explanations of cellular phenotypes including concept, mechanism, regulation, and detection methods in Chinese academic writing.
55
63%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Passed
No findings from the security scan
Fix and improve this skill with Tessl
tessl review fix ./scientific-skills/Evidence Insight/phenotype-introduction/SKILL.mdscripts/example.py is the most direct path to complete the request.phenotype-introduction package behavior rather than a generic answer.scripts/example.py plus 1 additional script(s).references/ for task-specific guidance.assets/example_asset.txt.Python: 3.10+. Repository baseline for current packaged skills.Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.cd "20260316/scientific-skills/Evidence Insight/phenotype-introduction"
python -m py_compile scripts/example.py
python scripts/example.py --helpExample run plan:
CONFIG block or documented parameters if the script uses fixed settings.python scripts/example.py with the validated inputs.See ## Overview above for related details.
scripts/example.py with additional helper scripts under scripts/.references/ contains supporting rules, prompts, or checklists.assets/.This skill generates detailed academic introductions for biomedical phenotypes with strict content requirements and word count constraints. It produces structured academic content with four mandatory sections:
When a user requests a phenotype introduction:
Include:
Include:
Include:
Include:
Strict academic structure:
1. Concept
[Content ≥800 words]
2. Mechanism and Occurrence Process
[Content ≥800 words]
3. Regulation
Regulation: [Regulatory content]
Phenotype Crosstalk: [Crosstalk content]
4. Markers and Detection Methods
Molecule: [Marker name]; Principle: [Detection principle]; Methods: [Detection method]
Molecule: [Marker name]; Principle: [Detection principle]; Methods: [Detection method]
[Repeat for ≥5 markers]All outputs must pass validation for:
f5ef65b
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.