SLXD AI API Pricing

Searches the catalogue of AI models and returns their current prices, with a confidence level and the sources backing each price.

Returns every current price for one model — input, output, cached reads, batch and priority tiers, context brackets — with the confidence level and which sources agree. By default these are the maker's own prices; pass `channel` to get what a reseller charges for the same model instead. Two dimensions can share a label, so the ones that would collide carry their qualifiers, e.g. 'Web search (context size: high)'.

Returns the current prices of several models side by side. Amounts in credits are never converted to money, so a credit-billed model is not comparable to a token-billed one. Two dimensions can share a label, so the ones that would collide carry their qualifiers, e.g. 'Web search (context size: high)'.

Returns a model's price over time. Each point is [date, amount] with the date as YYYY-MM-DD. The series holds only the points where the price CHANGED — prices are step functions, so a stable model is one point, not one per day; when a price changed twice on one day, both points are returned with the same date, in order. One series per price dimension: two dimensions can share a label, so the ones that would collide carry their qualifiers, e.g. 'Web search (context size: high)'.

Lists recent price increases, decreases, additions and removals across the catalogue, newest first.

Lists every provider in the catalogue and how many models each has. These are the houses that MAKE the models: a reseller (Vertex, Bedrock, Azure, OpenRouter, a subscription plan) is a sales channel, not a provider — ask `get_model_price` with a `channel` for what one of those charges.

Takes no parameters.

Explains where the prices come from: which sources are consulted, their weight and licence, when each last succeeded, and whether any is currently failing. Use this to judge how much to trust a price.

Takes no parameters.

Searches the full catalogue of available tools by keyword and returns the matching tool names with a short description. Use it when no directly-listed tool fits the task — many tools are available but not listed. Then call tool_schema for the one you picked, and run_tool to execute it.

Returns the full input schema of a single tool, including which arguments are required. Call it after find_tools and before run_tool.

Executes a tool by name with the given arguments. Use it for tools that are not directly listed — look them up with find_tools and check their arguments with tool_schema first. Prefer a directly-listed tool whenever one fits. If the action is destructive, ask the user to confirm before calling it.