[FEATURE] AgentCore Harness: expose prompt caching (Strands cache_config) as a Harness-level config option

Is your feature request related to a problem? Please describe.

There's no way to enable Bedrock prompt caching on an AgentCore Harness today. The underlying Strands Agents framework supports it — BedrockModel(cache_config=CacheConfig(strategy="auto")) emits cachePoint blocks into the Converse request — and Bedrock itself supports per-content-block cache checkpoints. But the Harness API's HarnessBedrockModelConfig.additionalParams is a passthrough to Bedrock Converse request fields, NOT to Strands framework kwargs, so there's no user-controllable path to the cache_config knob.

Empirical repro from a Console Harness playground call:

aws bedrock-agentcore-control update-harness \
  --model 'bedrockModelConfig={
    modelId=global.anthropic.claude-sonnet-4-6,
    additionalParams={cache_config={strategy=auto}}
  }'

The additionalParams value ends up as a top-level field on Bedrock's Converse API request, which rejects it:

Parameter validation failed:
Unknown parameter in input: "cache_config",
must be one of: modelId, messages, system, inferenceConfig, toolConfig,
guardrailConfig, additionalModelRequestFields, promptVariables,
additionalModelResponseFieldPaths, requestMetadata, performanceConfig,
serviceTier, outputConfig

That error confirms two things:

1. additionalParams maps 1:1 to Bedrock Converse request fields.
2. Cache configuration doesn't exist at the Converse level — it's per-content-block (cachePoint markers inside system/messages/tools), which the Strands framework emits before firing Bedrock. Without a way to talk to the framework, caching stays off.

Cost impact. For our ADAPT pipeline (multi-stage MEC error correction agent), each invocation runs ~40–75 model turns with a 150K plateau input-token conversation context, re-billed as fresh input every turn. That's **$19–25/session** today. Enabling cache_config="auto" on the stable ~10K-token system prompt would drop this to ~$5–6 (roughly 75% saving). At production target of ~200 issues/day this is the difference between ~$450/day and ~$1,900/day. Every stable-system-prompt workload on managed Harness pays this cost.

Describe the solution you'd like

A Harness-level prompt caching config that the managed Strands runtime picks up and translates into cachePoint markers on the Converse request. Two possible shapes:

Option A — dedicated field (cleaner, no doc contract change):

{
  "bedrockModelConfig": {
    "modelId": "global.anthropic.claude-sonnet-4-6",
    "promptCaching": {
      "strategy": "auto",
      "ttl": "5m"
    }
  }
}

Option B — framework-kwargs passthrough (would require semantic split from today's additionalParams, since that's Converse passthrough):

{
  "bedrockModelConfig": {
    "modelId": "global.anthropic.claude-sonnet-4-6",
    "frameworkParams": {
      "cache_config": {"strategy": "auto"}
    }
  }
}

Semantics that would match Strands directly: strategy ∈ {"auto", "anthropic"}, optional ttl ("5m" / "1h"), and optionally cache_tools for tool-schema caching (also supported by Strands' BedrockModel).

Describe alternatives you've considered

1. Bring-your-own agent runtime — skip the managed Harness path and deploy a custom AgentCore Runtime container with self-managed Strands where cache_config is set at BedrockModel construction. Big architectural change; loses what Harness gives (managed microVM per session, tool routing, memory config, InvokeHarness single-call API).
2. Fork Strands and set cache_config unconditionally — the managed Harness runtime pins its own Strands version, so a user fork doesn't apply.
3. additionalParams.additionalModelRequestFields.anthropic_beta = ["prompt-caching-2024-07-31"] — activates the model-level capability, but the request still needs per-content-block cache_control markers that Strands isn't emitting.
4. AWS support ticket — contract-level path, no public paper trail; not useful for other customers hitting the same gap.

Additional context

• Strands cache support: BedrockModel.cache_config parameter in strands-agents/harness-sdk
• Bedrock prompt caching reference: https://docs.aws.amazon.com/bedrock/latest/userguide/prompt-caching.html
• Terraform provider gap for the same overall class of pass-through knobs: hashicorp/terraform-provider-aws#48363
• Related in this repo: #648 — environmentVariables not injected into microVM process env

For managed Harness, this is the biggest cost lever available for stable-prompt agent workloads. Every large-context multi-turn agent will re-pay for the same ~10K–50K system prompt every turn until the framework layer gets a way to opt into caching.

Start with strands-py/src/strands/models/bedrock.py and its BedrockModel.cache_config parameter, then trace the HarnessBedrockModelConfig and additionalParams entry points described in the issue. Done means a documented Harness-level option reaches the managed Strands runtime, produces cachePoint markers in Converse requests, and supports the stated strategy and TTL semantics.