tokenlab-model-pickerlisted

# TokenLab Model Picker Use this skill when a user asks which TokenLab model to use, how to compare model options, or how to route a workload across model families. ## What this skill should deliver - A short model shortlist with exact TokenLab model IDs. - The workload assumptions used to pick the models. - A public catalog lookup path that the user or agent can rerun. - A fallback model when the first choice is unavailable or too expensive. - A caveat when a recommendation depends on volatile pricing, availability, or benchmark data. ## Preferred approach 1. Identify the workload: chat, coding, agent loop, image, video, audio, embedding, rerank, translation, or multimodal. 2. Use the public model catalog before recommending hardcoded IDs: - General catalog: `GET https://api.tokenlab.sh/v1/models` - Task shortlist: `GET https://api.tokenlab.sh/v1/models?recommended_for=<scene>` - Model contract: `GET https://api.tokenlab.sh/v1/models/:model` - Pricing detail: `GET https://api.tokenlab.sh/v1/models/:model/pricing` 3. Prefer exact public model IDs over family names. 4. Separate recommendation dimensions: - quality or frontier capability - cost sensitivity - latency or fast iteration - native endpoint needs - multimodal input or output 5. Return a compact table, then one runnable API example if useful. ## Default shortlist patterns - Coding and agent work: choose a strong reasoning/coding model, a cheaper fallback, and a fast iteration model. -