Source: https://github.com/aipoch/medical-research-skills
Phenotype Introduction
When to Use
- Use this skill when you need "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." in a reproducible workflow.
- Use this skill when a evidence insight task needs a packaged method instead of ad-hoc freeform output.
- Use this skill when the user expects a concrete deliverable, validation step, or file-based result.
- Use this skill when
scripts/example.py is the most direct path to complete the request.
- Use this skill when you need the
phenotype-introduction package behavior rather than a generic answer.
Key Features
- Scope-focused workflow aligned to: "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.".
- Packaged executable path(s):
scripts/example.py plus 1 additional script(s).
- Reference material available in
references/ for task-specific guidance.
- Reusable packaged asset(s), including
assets/example_asset.txt.
- Structured execution path designed to keep outputs consistent and reviewable.
Dependencies
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.
Example Usage
cd "20260316/scientific-skills/Evidence Insight/phenotype-introduction"
python -m py_compile scripts/example.py
python scripts/example.py --help
Example run plan:
- Confirm the user input, output path, and any required config values.
- Edit the in-file
CONFIG block or documented parameters if the script uses fixed settings.
- Run
python scripts/example.py with the validated inputs.
- Review the generated output and return the final artifact with any assumptions called out.
Implementation Details
See ## Overview above for related details.
- Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
- Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
- Primary implementation surface:
scripts/example.py with additional helper scripts under scripts/.
- Reference guidance:
references/ contains supporting rules, prompts, or checklists.
- Packaged assets: reusable files are available under
assets/.
- Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
- Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Overview
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:
- Concept
- Mechanism and occurrence process
- Regulation
- Marker detection methods
Quick Start
When a user requests a phenotype introduction:
- Parse the phenotype name from the user query.
- Generate Concept section (≥800 words) including definition, biological characteristics, cellular functions, and historical background.
- Generate Mechanism section (≥800 words) describing occurrence process, cellular impacts, and key molecular components.
- Generate Regulation section (≥800 words) covering regulatory principles, molecular pathways, and phenotype crosstalk.
- Generate Marker Detection section (≥500 words) listing ≥5 key markers with detection principles and methods.
- Format output using strict academic structure.
Content Requirements
1. Concept Section (≥800 words)
Include:
- Detailed phenotype definition
- Biological characteristics
- Cellular-level functions and roles
- Historical development and background
2. Mechanism Section (≥800 words)
Include:
- How the phenotype occurs
- Cellular impacts and downstream effects
- Key molecular components
- Step-by-step occurrence description
3. Regulation Section (≥800 words)
Include:
- Regulatory principles
- Participating molecules and signaling pathways
- Crosstalk with other phenotypes
- Nested or hierarchical relationships
4. Marker Detection Section (≥500 words, ≥5 markers)
Include:
- List of key marker molecules
- Detection rationale for each marker
- Common detection methods
Output Format
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]
Quality Control
All outputs must pass validation for:
- Word count per section
- Minimum 5 marker molecules
- Proper academic terminology
- Complete section coverage
- Logical scientific consistency
1---2name: phenotype-introduction3description: 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.4license: MIT5---6> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)
7
8# Phenotype Introduction
9
10## When to Use
11
12- Use this skill when you need "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." in a reproducible workflow.
13- Use this skill when a evidence insight task needs a packaged method instead of ad-hoc freeform output.
14- Use this skill when the user expects a concrete deliverable, validation step, or file-based result.
15- Use this skill when `scripts/example.py` is the most direct path to complete the request.
16- Use this skill when you need the `phenotype-introduction` package behavior rather than a generic answer.
17
18## Key Features
19
20- Scope-focused workflow aligned to: "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.".
21- Packaged executable path(s): `scripts/example.py` plus 1 additional script(s).
22- Reference material available in `references/` for task-specific guidance.
23- Reusable packaged asset(s), including `assets/example_asset.txt`.
24- Structured execution path designed to keep outputs consistent and reviewable.
25
26## Dependencies
27
28- `Python`: `3.10+`. Repository baseline for current packaged skills.
29- `Third-party packages`: `not explicitly version-pinned in this skill package`. Add pinned versions if this skill needs stricter environment control.
30
31## Example Usage
32
33```bash
34cd "20260316/scientific-skills/Evidence Insight/phenotype-introduction"
35python -m py_compile scripts/example.py
36python scripts/example.py --help
37```
38
39Example run plan:
401. Confirm the user input, output path, and any required config values.
412. Edit the in-file `CONFIG` block or documented parameters if the script uses fixed settings.
423. Run `python scripts/example.py` with the validated inputs.
434. Review the generated output and return the final artifact with any assumptions called out.
44
45## Implementation Details
46
47See `## Overview` above for related details.
48
49- Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
50- Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
51- Primary implementation surface: `scripts/example.py` with additional helper scripts under `scripts/`.
52- Reference guidance: `references/` contains supporting rules, prompts, or checklists.
53- Packaged assets: reusable files are available under `assets/`.
54- Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
55- Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
56
57## Overview
58
59This skill generates detailed academic introductions for biomedical phenotypes with strict content requirements and word count constraints.
60It produces structured academic content with four mandatory sections:
61
621. Concept
632. Mechanism and occurrence process
643. Regulation
654. Marker detection methods
66
67---
68
69## Quick Start
70
71When a user requests a phenotype introduction:
72
731. Parse the phenotype name from the user query.
742. Generate **Concept section** (≥800 words) including definition, biological characteristics, cellular functions, and historical background.
753. Generate **Mechanism section** (≥800 words) describing occurrence process, cellular impacts, and key molecular components.
764. Generate **Regulation section** (≥800 words) covering regulatory principles, molecular pathways, and phenotype crosstalk.
775. Generate **Marker Detection section** (≥500 words) listing ≥5 key markers with detection principles and methods.
786. Format output using strict academic structure.
79
80---
81
82## Content Requirements
83
84### 1. Concept Section (≥800 words)
85
86Include:
87
88* Detailed phenotype definition
89* Biological characteristics
90* Cellular-level functions and roles
91* Historical development and background
92
93---
94
95### 2. Mechanism Section (≥800 words)
96
97Include:
98
99* How the phenotype occurs
100* Cellular impacts and downstream effects
101* Key molecular components
102* Step-by-step occurrence description
103
104---
105
106### 3. Regulation Section (≥800 words)
107
108Include:
109
110* Regulatory principles
111* Participating molecules and signaling pathways
112* Crosstalk with other phenotypes
113* Nested or hierarchical relationships
114
115---
116
117### 4. Marker Detection Section (≥500 words, ≥5 markers)
118
119Include:
120
121* List of key marker molecules
122* Detection rationale for each marker
123* Common detection methods
124
125---
126
127## Output Format
128
129Strict academic structure:
130
131```
1321. Concept
133
134[Content ≥800 words]
135
1362. Mechanism and Occurrence Process
137
138[Content ≥800 words]
139
1403. Regulation
141
142Regulation: [Regulatory content]
143
144Phenotype Crosstalk: [Crosstalk content]
145
1464. Markers and Detection Methods
147
148Molecule: [Marker name]; Principle: [Detection principle]; Methods: [Detection method]
149
150Molecule: [Marker name]; Principle: [Detection principle]; Methods: [Detection method]
151
152[Repeat for ≥5 markers]
153```
154
155---
156
157## Quality Control
158
159All outputs must pass validation for:
160
161* Word count per section
162* Minimum 5 marker molecules
163* Proper academic terminology
164* Complete section coverage
165* Logical scientific consistency