/**
 * buildCacheSubflow — the per-turn prompt-cache decision, as ONE subflow.
 *
 * Collapses the cache machinery into a single `sf-cache` boundary so the
 * agent chart reads cleanly (one "Cache" box you can drill into) while the
 * execution tree stays honest:
 *
 *     decideCacheMarkers  →  CacheGate (decider)  →  ApplyMarkers / SkipCaching
 *
 * Layering (see src/cache/types.ts):
 *   - This subflow is the provider-AGNOSTIC DECISION layer — it only computes
 *     and gates provider-neutral `CacheMarker[]`. It knows nothing about any
 *     provider.
 *   - The provider-SPECIFIC MECHANISM (Anthropic `cache_control`, OpenAI
 *     automatic, …) is the attached provider's `CacheStrategy`, selected by
 *     `provider.name`, applied later when the request is built.
 *
 * Why `UpdateSkillHistory` is NOT in here: the `skillHistory` rolling window
 * must persist across loop iterations. Keeping `UpdateSkillHistory` in the
 * main loop (just before this subflow) lets `skillHistory` live in the parent
 * scope without round-tripping through this subflow's in/out mappers — the
 * subflow stays pure (reads the turn's state, writes only `cacheMarkers`).
 *
 * Deps-free: every input (`activeInjections`, `iteration`, `skillHistory`,
 * `recentHitRate`, `systemPromptCachePolicy`, …) is supplied by the PARENT's
 * `inputMapper` at the mount site; the output is just `cacheMarkers`.
 */
import { type FlowChart } from 'footprintjs';
/**
 * Build the `sf-cache` subflow chart. Called by `buildAgentChart` and
 * `buildDynamicAgentChart` and mounted via `addSubFlowChartNext(
 * SUBFLOW_IDS.CACHE, buildCacheSubflow(), 'Cache', { inputMapper,
 * outputMapper, arrayMerge: Replace })`.
 */
export declare function buildCacheSubflow(): FlowChart;