import { PlannerConfig } from "../contracts/planner/planner-config.type.mjs";
import { PlannerContract } from "../contracts/planner/planner.contract.mjs";

//#region ../ai/src/planner/planner.d.ts
/**
 * `ai.planner(config)` — construct a {@link PlannerContract}.
 *
 * Validates the config at author time (throws {@link PlannerFailedError}
 * on a bad shape), builds (or adopts) the plan-generation agent, computes
 * a stable structural signature, and returns an instance satisfying
 * `ExecutableContract` so the planner composes into supervisors,
 * orchestrators, and outer agents through the same uniform surface.
 *
 * At `execute(goal)` the planner asks its LLM for an ordered plan over
 * the registered `capabilities`, then executes that plan step-by-step
 * through each capability's own `execute()` — reusing the existing
 * executable machinery rather than forking it — and returns the unified
 * `{ data, report, usage, error }` envelope with `report.type ===
 * "planner"`.
 *
 * @example
 * const research = ai.planner({
 *   name: "research-assistant",
 *   model: ai.openai.model({ name: "gpt-4o" }),
 *   capabilities: [
 *     { name: "search", description: "Search the web", executable: searchAgent },
 *     { name: "write", description: "Draft a summary", executable: writerAgent },
 *   ],
 *   maxSteps: 6,
 * });
 *
 * const { data, report } = await research.execute("Compare React vs Vue in 2026");
 */
declare function planner<TOutput = unknown>(config: PlannerConfig<TOutput>): PlannerContract<TOutput>;
//#endregion
export { planner };
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