ai_member_xiaoyan/skills/task-router/SKILL.md

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---
name: dialogue-components-standardizer
description: A unified skill for standardizing the production and review of 6 dialogue interaction components. Core logic is fixed; optimizations are handled via branch files and scripts for repeatability. Enter skill only when components change dynamically.
---
# Dialogue Components Standardizer
## Overview
This skill provides a modular structure for standardizing dialogue components:
- **Core (Fixed)**: Component types, workflows, and policies (defined here).
- **Branch Files**: `component_configs.yaml` for component-specific details (modify for optimizations).
- **Scripts**: Automated execution for repeatable tasks (e.g., generation, review).
- **Dynamic Entry**: Use skill for component changes; otherwise, rely on scripts.
## Core Structure
### Component Types (Fixed)
The 6 components are predefined:
1. dialogue_reading
2. dialogue_expression
3. dialogue_selective_reading
4. dialogue_selection
5. dialogue_sentence_building
6. dialogue_fill_in_the_blanks
### Workflows (Fixed)
- **Production**: Generate configs via script.
- **Review**: Validate via script.
- **Optimization**: Update `component_configs.yaml` for details.
## Branch Files
- `component_configs.yaml`: Contains format, config, and validation rules per component. Modify this for optimizations without altering core.
## Scripts
- `scripts/generate_component.py`: Generates component configs (repeatable).
- `scripts/review_component.py`: Reviews and validates configs (repeatable).
## Usage
1. For standard production: Run scripts directly.
2. For component changes: Enter skill to update core or branch files.
3. Optimize details: Edit `component_configs.yaml`.
## Examples
- Generate: `python3 scripts/generate_component.py --type dialogue_reading --output config.json`
- Review: `python3 scripts/review_component.py --file config.json`
- "Rewrite this paragraph to sound more professional."
Route: `low_compute_model`
- "Design the data-cleaning approach, then process the CSV."
Route: `high_compute_model`, then `python_script`
## Resources
- Use [route_request.py](/Users/shasha/.codex/skills/task-router/scripts/route_request.py) as the first-pass classifier and execution planner.