Agent Harness API

fharness is the top-level orchestration layer for long-running agent workflows in Fiddlesticks.

It currently supports:

• initializer flow
• task agent incremental loop
• runtime wiring + run-level policy
• reliability + guardrails for production usage

fharness composes lower layers (fmemory, fchat, ftooling, fprovider) into a structured multi-run harness.

Responsibilities

• Run initializer setup for a session (manifest + feature list + progress + checkpoint)
• Run incremental task iterations one feature at a time
• Enforce clean handoff by recording explicit run outcomes
• Coordinate health checks, execution, validation, and persistence updates

fharness does not:

• Implement provider transports (fprovider)
• Implement turn orchestration internals (fchat)
• Implement tool runtimes (ftooling)
• Implement persistence internals (fmemory)

Add dependency

[dependencies]
fharness = { path = "../fharness" }
fmemory = { path = "../fmemory" }
fchat = { path = "../fchat" }

Core types

• Harness: orchestrator for initializer and task iterations
• HarnessBuilder: runtime wiring for provider/chat/tooling/memory
• InitializerRequest / InitializerResult
• TaskIterationRequest / TaskIterationResult
• RuntimeRunRequest / RuntimeRunOutcome
• HealthChecker (NoopHealthChecker default)
• OutcomeValidator (AcceptAllValidator default)
• FeatureSelector (FirstPendingFeatureSelector default)
• HarnessError / HarnessErrorKind

Initializer flow

run_initializer(...):

1. Validates objective and feature list rules
2. Builds/versions SessionManifest
3. Uses initialize_session_if_missing(...) for idempotent initialization
4. Persists initial progress + run checkpoint

If no feature list is provided, Harness generates a starter skeleton via starter_feature_list(...).

use std::sync::Arc;

use fharness::{Harness, InitializerRequest};
use fmemory::{InMemoryMemoryBackend, MemoryBackend};

let memory: Arc<dyn MemoryBackend> = Arc::new(InMemoryMemoryBackend::new());
let harness = Harness::new(memory);

let request = InitializerRequest::new("session-1", "run-init-1", "Build incremental harness");
let _result = harness.run_initializer(request).await?;

Task-Iteration incremental loop

run_task_iteration(...) executes one bounded run:

1. Get bearings
   • loads manifest/progress/features from fmemory
   • runs health check using manifest init_plan
2. Picks one highest-priority failing feature (passes == false)
3. Delegates execution to fchat (run_turn or stream_turn)
4. Validates outcome via OutcomeValidator
5. Updates artifacts:
   • marks feature passing only when validated
   • appends progress entry
   • records completed checkpoint with status/note

Integrated runtime and policy ownership

HarnessBuilder wires lower-layer runtime dependencies directly:

• provider (fprovider)
• chat service (fchat) with transcript storage from fmemory
• tool runtime (ftooling)
• memory backend (fmemory)

fchat stays responsible for turn orchestration. fharness owns run-level policy:

• phase selection (initializer vs task-iteration)
• feature selection strategy (FeatureSelector)
• validation gate before marking feature pass (OutcomeValidator)

Reliability + guardrails

Harness run policy now supports reliability constraints:

• mode (strict_incremental, bounded_batch, unlimited_batch)
• max_turns_per_run
• max_features_per_run (used by strict/bounded modes)
• retry_budget
• fail-fast conditions (health check, chat, validation)

Mode semantics:

• strict_incremental: exactly one feature per run (max_features_per_run must be 1)
• bounded_batch: process up to max_features_per_run features in one run
• unlimited_batch: process features until completion gate or turn/retry constraints stop progress

Completion guardrail:

• harness does not declare done early
• completion requires all required features in feature_list to have passes = true

use std::sync::Arc;

use fharness::{Harness, RuntimeRunRequest, RuntimeRunOutcome};
use fmemory::{InMemoryMemoryBackend, MemoryBackend};

let memory: Arc<dyn MemoryBackend> = Arc::new(InMemoryMemoryBackend::new());
let harness = Harness::builder(memory)
    .provider(provider)
    .tool_runtime(tool_runtime)
    .build()?;

match harness.run(RuntimeRunRequest::new(session, "run-1", "Build feature loop")).await? {
    RuntimeRunOutcome::Initializer(_) => {
        // session bootstrapped
    }
    RuntimeRunOutcome::TaskIteration(result) => {
        // one task iteration completed
        assert!(result.validated);
    }
}

use std::sync::Arc;

use fharness::{Harness, TaskIterationRequest};

let harness = Harness::new(memory).with_chat(chat_service);
let request = TaskIterationRequest::new(session, "run-task-1");
let _result = harness.run_task_iteration(request).await?;

Extensibility hooks

• HealthChecker
  • run startup/baseline checks before task-iteration work
• OutcomeValidator
  • enforce real validation gates before marking features as passing

Use with_health_checker(...) and with_validator(...) to override defaults.

Clean handoff guarantees

Every task-iteration run records terminal outcome artifacts:

• run checkpoint with explicit status (Succeeded/Failed) and note
• progress entry summarizing what happened

This avoids ambiguous handoff state across context windows.

Error model

HarnessErrorKind variants:

• InvalidRequest
• Memory
• Chat
• Validation
• HealthCheck
• NotReady