Free LLM Navigator
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About this skill
What It Solves
Choosing free LLMs is tedious: quotas, context limits, multimodal support, stability, and free-tier policies change frequently. Developers usually need a quick answer to questions like “which models are currently available,” “which one fits Chinese chat, coding, or reasoning,” “how do I get the API key,” and “does it work after configuration.” This skill consolidates those steps into a conversational workflow, reducing back-and-forth across docs, signup pages, configs, and debugging.
How It Works
- Intent routing: When a user mentions “find free models,” “recommend a free API,” or similar intents, the skill triggers a search and recommendation flow.
- Information aggregation: It uses
WebSearchto collect the latest free LLM API quota information and readsreferences/free_models_table.mdto present model lists, scores, and scenario routing. - Model operations: It supports commands such as
compare,detail,apikey-guide,configure,test,recommend, anddiagnose, covering comparison, signup guidance, configuration, connectivity checks, and troubleshooting. - Scenario routing: It suggests primary and fallback models by use case, for example
GLM-4-Flashfor Chinese conversation,DeepSeek V3for coding,DeepSeek R1for reasoning or math, andGemini 2.5 Profor long documents or multimodal tasks. - Switching execution: When a user explicitly asks to switch, it can call
session_status(model="provider/model-id")to set the current session model and run an automatic test.
Boundaries
- Free quotas, signup rules, and model availability can change; results should be verified against live search and official pages.
- For expiring models, the skill estimates remaining days from the current conversation time, but it does not replace provider account status.
- This skill is intended for developers who need fast free-model selection and validation. It is not a production-only dependency and does not guarantee that a model remains free or consistently high-quality.
Use Cases
- Before onboarding an LLM, compare free quota, context length, and fit for Chinese chat, coding, or reasoning to shortlist candidates.
- After obtaining an API key, configure a provider/model and immediately send a test request to verify it can be used in the session.
- When model calls fail, run diagnostics to check connectivity, authentication, and configuration fields, then fix or switch to a fallback model.
- For Chinese chat, coding, reasoning, or long-document tasks, select recommended models and rank primary and fallback options to reduce trial and error.
Best For
- Indie developers who need to quickly verify whether a free LLM is usable
- AI application engineers who need to select and switch among multiple free models
- Algorithm engineers who need to configure API keys and troubleshoot model calls
- Prompt engineers who need to choose models for Chinese, coding, or reasoning scenarios
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