bio-task-system

SkillMedia

Identify the main task categories in the field and organize them into a staged difficulty ladder.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the bio-task-system skill

About this capability

A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.

What this skill tells your AI

The instructions your AI receives, as published by biotender-max/awesome-bio-agent-skills in skills/bioclaw/bio-task-system/SKILL.md and read by ahel’s review.

Step 2: Task system design (任务体系构建)

Identify the main task categories in the field and organize them into a staged difficulty ladder.

Purpose

  1. Find the dominant task taxonomy in the target field
  2. Define Level 1-4 task tiers
  3. Ensure the task ladder increases in difficulty
  4. Prepare the task system for downstream dataset and metric design

Input Format

topic: [research topic]
paper_count: [number of related papers from Step 1]

Workflow

Step 2.1: Task taxonomy search

If there is substantial prior work, extract tasks from existing papers.

If there is not enough prior work, borrow the taxonomy from a parent domain and adapt it.

Typical adaptation logic:

  • single-cell multi-omics -> spatial multi-omics
  • modality alignment -> spatial-cell alignment
  • batch integration -> cross-sample integration

Step 2.2: Task tier design

Define four levels:

  • Level 1: basic validation task
  • Level 2: intermediate application task
  • Level 3: challenge task
  • Level 4: flagship innovation task

Increase across three dimensions:

  1. Data complexity
  2. Technical difficulty
  3. Biological value

Step 2.3: Standardize task descriptions

For each task, write:

  • definition
  • difficulty level
  • data requirements
  • technical focus
  • biological value
  • representative methods
  • mapped figure

Output Format

# Task System Design

## Task Sources
- Extracted from related papers:
- Borrowed from parent domain:

## Tier Overview
| Level | Task type | Difficulty | Figure |
|-------|-----------|------------|--------|
| 1 | ... | low | Figure 2 |
| 2 | ... | medium | Figure 3 |
| 3 | ... | high | Figure 4 |
| 4 | ... | highest | Figure 5 |

## Detailed Task Descriptions

### Task 1: [task name]
- Definition:
- Difficulty:
- Data requirements:
- Technical focus:
- Biological value:
- Representative methods:
- Mapped figure:

### Task 2: ...

## Progression Rationale
1. Data complexity rises across tasks
2. Technical difficulty rises across tasks
3. Biological value rises across tasks

## Next Step
- Use the task system to search for datasets in Step 3

Example Ladder

  • Level 1: vertical integration
  • Level 2: horizontal / cross-slice integration
  • Level 3: mosaic integration with missing modalities
  • Level 4: diagonal integration across platform / resolution / cohort

Usage

/bio-task-system "spatial multi-omics integration | paper_count: 5"

Notes

  1. Keep the ladder interpretable to reviewers.
  2. Avoid adding too many tasks; four well-designed tiers are usually enough.
  3. Make sure each task can later be tied to datasets, metrics, and figures.

Signals

GitHub stars
178
Forks
32
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
bio-task-system
Source
github.com/biotender-max/awesome-bio-agent-skills