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- China Model Selection Guide
china-model-selection-guide_skill
- Python
0
GitHub Stars
2
Bundled Files
2 months ago
Catalog Refreshed
3 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill hexbee/hello-skills --skill china-model-selection-guide- openai.yaml321 B
- SKILL.md2.3 KB
Overview
This skill provides a compact China-focused model selection and task-routing guide for Doubao-Seed-2.0-Code, GLM-5, MiniMax-M2.5, and Kimi-K2.5. It helps teams pick the best-fit model based on input type, task complexity, engineering constraints, and delivery goals. The skill also defines a default multi-model pipeline for staged projects and mandates a consistent recommendation output format.
How this skill works
The guide first triages by input type (visual, long-text, structured prompts) and task complexity (reasoning, cross-language, execution-heavy). It applies tie-break rules that prioritize hard constraints (vision, long context, cross-language, agentic planning), then cost/latency, then project phase to select primary and fallback models. For composite tasks it prescribes a default pipeline: GLM-5 for planning, Doubao for visual/frontend, MiniMax for backend/automation, and Kimi for large-document handoff. Every recommendation includes decision, rationale, risks, and an execution-ready prompt draft.
When to use it
- Choosing a single model for a new engineering or product task
- Designing a staged pipeline that uses multiple models per phase
- Routing tasks according to input modality (images, long text, code)
- Balancing quality versus latency and cost under engineering constraints
- Preparing handoff prompts and rollback strategies for production
Best practices
- Start by answering two triage questions: core input type and task complexity
- Prioritize hard constraints (vision, long-context, cross-language) before cost
- Use GLM-5 for architecture, decomposition, and agentic planning
- Route visual/frontend work to Doubao-Seed-2.0-Code and cross-language code to MiniMax-M2.5
- Send large document sets or full codebase handoffs to Kimi-K2.5 for downstream tasks
Example use cases
- Build a UI mockup-to-code pipeline: Doubao primary, MiniMax fallback for integration scripts
- Refactor a multilingual codebase: plan with GLM-5, implement cross-language patches with MiniMax
- Process dozens of technical docs for release notes and API docs: Kimi-K2.5 primary
- Complex system design and agent planning: GLM-5 primary with Kimi for documentation handoff
- Multi-phase product delivery: planning (GLM-5) → frontend (Doubao) → backend (MiniMax) → docs (Kimi)
FAQ
Follow tie-break rules: satisfy hard constraints first, then compare cost/latency, and finally split by project phase to allow multi-model routing.
How should recommendations be presented?
Always include: Decision (primary + fallback), Rationale mapped to input/constraints, Risks and rollback strategy, and an execution-ready prompt draft.