tokenlab-cost-routinglisted

# TokenLab Cost Routing Use this skill when a user asks how to reduce TokenLab cost, compare model prices, pick fallbacks, or route requests by quality, latency, and budget. ## What this skill should deliver - A compact routing recommendation with exact public TokenLab model IDs. - A cost-aware fallback chain for the user's workload. - A catalog/pricing lookup path that can be rerun. - A note on which endpoint family each model should use. - Guardrails for when not to switch models because doing so would change output, safety, or request semantics. ## Preferred approach 1. Identify the workload and constraints: - chat, coding, agent loop, image, video, audio, embedding, rerank, translation, or multimodal - quality floor - latency target - budget or cost ceiling - native endpoint requirement 2. Read live public catalog signals before recommending: - `GET https://api.tokenlab.sh/v1/models` - `GET https://api.tokenlab.sh/v1/models?recommended_for=<scene>` - `GET https://api.tokenlab.sh/v1/models/:model` - `GET https://api.tokenlab.sh/v1/models/:model/pricing` 3. Build a chain with roles: - primary quality model - balanced default - fast fallback - budget fallback 4. If the user asks for exact cost, compute from live pricing and their estimated token/media volume. State units and assumptions. 5. For non-chat requests, inspect model details before changing parameters or endpoint family. ## Output format - One sentence stating workload