Agent skill · AI & Agents

agf-wiring-multi-llm-sdk

Use when wiring up or switching between China-domestic LLM providers (DeepSeek, Doubao/Volc Ark, Qwen/DashScope, MiniMax). Provides OpenAI-compatible adapter pattern, env-var contracts, fallback strategy, cost guardrails, and minimum verifications before declaring integration done.

pcliangx359★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add pcliangx/AppGenesisForge --skill agf-wiring-multi-llm-sdk --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Path: .claude/skills/agf-wiring-multi-llm-sdk/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 359
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Wiring Multi-LLM SDK (DeepSeek / Doubao / Qwen / MiniMax) Use this skill when: - You add a new LLM provider to `backend/app/agents/` or any backend module - You switch the default provider (e.g. DeepSeek → Doubao for cost reasons) - You wire fallback / retry logic between providers - You suspect a provider mismatch is the cause of a bug ## Decision: which SDK style? All four providers expose **O

More from AppGenesisForge
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About this skill
What does the agf-wiring-multi-llm-sdk skill do?

Use when wiring up or switching between China-domestic LLM providers (DeepSeek, Doubao/Volc Ark, Qwen/DashScope, MiniMax). Provides OpenAI-compatible adapter pattern, env-var contracts, fallback strategy, cost guardrails, and minimum verifications before declaring integration done.

How do I install it?

Run `npx skills add pcliangx/AppGenesisForge --skill agf-wiring-multi-llm-sdk --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From pcliangx/AppGenesisForge, a repository with 359 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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