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# Adaptive change evaluation
This suite exercises the `adaptive-engineering` profile on a bounded but nontrivial correctness change. The root must keep ownership of diagnosis and integration, use a specialist only where it adds value, and obtain independent review before claiming success.
The native scout is intentionally not a worker assertion: native Codex participation is not represented in Agent MCP job telemetry. The evaluator does require the MCP implementation and review roles and measures whether their results were consumed.
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# Ledger invariants
`Ledger.apply(operation_id, account, delta)` applies an operation at most once globally.
- A successful operation permanently consumes its operation ID.
- A rejected overdraft must not consume its operation ID.
- A caller may fund the account and retry the same rejected operation.
- Balances may never become negative.
- Duplicate successful operations return the current balance without applying the delta again.
The current implementation violates the rejected-operation rule.
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class Ledger:
def __init__(self) -> None:
self._balances: dict[str, int] = {}
self._applied: set[str] = set()
def balance(self, account: str) -> int:
return self._balances.get(account, 0)
def apply(self, operation_id: str, account: str, delta: int) -> int:
if operation_id in self._applied:
return self.balance(account)
self._applied.add(operation_id)
updated = self.balance(account) + delta
if updated < 0:
raise ValueError("insufficient funds")
self._balances[account] = updated
return updated
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import unittest
from ledger import Ledger
class LedgerTests(unittest.TestCase):
def test_success_is_idempotent(self):
ledger = Ledger()
self.assertEqual(ledger.apply("deposit-1", "a", 10), 10)
self.assertEqual(ledger.apply("deposit-1", "a", 10), 10)
def test_overdraft_does_not_change_balance(self):
ledger = Ledger()
with self.assertRaises(ValueError):
ledger.apply("withdraw-1", "a", -4)
self.assertEqual(ledger.balance("a"), 0)
def test_rejected_operation_can_be_retried(self):
ledger = Ledger()
with self.assertRaises(ValueError):
ledger.apply("withdraw-1", "a", -4)
ledger.apply("deposit-1", "a", 10)
self.assertEqual(ledger.apply("withdraw-1", "a", -4), 6)
if __name__ == "__main__":
unittest.main()
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import unittest
from ledger import Ledger
class HoldoutLedgerTests(unittest.TestCase):
def test_rejected_id_remains_globally_available(self):
ledger = Ledger()
with self.assertRaises(ValueError):
ledger.apply("shared", "a", -1)
self.assertEqual(ledger.apply("shared", "b", 3), 3)
def test_successful_id_is_global_across_accounts(self):
ledger = Ledger()
ledger.apply("shared", "a", 3)
self.assertEqual(ledger.apply("shared", "b", 9), 0)
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import unittest
from ledger import Ledger
class HoldoutLedgerTests(unittest.TestCase):
def test_multiple_rejections_do_not_consume_id(self):
ledger = Ledger()
for _ in range(2):
with self.assertRaises(ValueError):
ledger.apply("withdraw", "a", -2)
ledger.apply("fund", "a", 4)
self.assertEqual(ledger.apply("withdraw", "a", -2), 2)
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schema_version = 8
id = "adaptive-change"
profile = "adaptive-engineering"
name = "Adaptive Engineering Change"
description = "Matched trials for selective delegation on decomposable and tightly coupled engineering work."
fixture = "fixture"
development_trials = 3
release_trials = 5
[promotion]
primary_metric = "success_rate"
direction = "higher"
strongest_success_tolerance = 0.02
minimum_relative_improvement = 0.10
minimum_absolute_improvement = 0.05
worker_minimum_success_contribution = 0.02
worker_minimum_metric_contribution = 0.10
no_regression_higher_metrics = []
no_regression_lower_metrics = []
require_complete_api_cost = true
[[variants]]
id = "configured-root"
purpose = "Configured Sol root with delegation mechanically disabled."
topology = "root_only"
comparison_class = "configured_root_alone"
[[variants]]
id = "strongest-task-single"
purpose = "Task-specific flagship Sol single-agent control."
profile = "adaptive-engineering"
topology = "root_only"
comparison_class = "strongest_single_agent"
[[variants]]
id = "codex-access-single"
purpose = "ChatGPT Codex access-service control."
profile = "adaptive-engineering"
topology = "root_only"
comparison_class = "access_service_single_agent"
access_product = "chatgpt_codex"
[[variants]]
id = "go-access-single"
purpose = "OpenCode Go economical DeepSeek control."
profile = "high-confidence-debugging"
topology = "root_only"
comparison_class = "access_service_single_agent"
access_product = "opencode_go"
[[variants]]
id = "zen-access-single"
purpose = "OpenCode Zen Claude control."
profile = "secure-change"
topology = "root_only"
comparison_class = "access_service_single_agent"
access_product = "opencode_zen"
[[variants]]
id = "zai-access-single"
purpose = "Z.AI Coding Plan GLM control."
profile = "incident-hypothesis-triage"
topology = "root_only"
comparison_class = "access_service_single_agent"
access_product = "zai_coding_plan"
[[variants]]
id = "openrouter-access-single"
purpose = "Pinned OpenRouter DeepSeek route control."
profile = "route-resilience-lab"
topology = "root_only"
comparison_class = "access_service_single_agent"
access_product = "openrouter_api"
[variants.bindings]
route_observer = "openrouter_openai_chat__deepseek_deepseek_v4_pro"
[[variants]]
id = "root-plus-implementation"
purpose = "Configured root plus the objectively testable implementation branch."
topology = "root_plus_worker"
worker = "implementation_specialist"
comparison_class = "root_plus_highest_value"
[[variants]]
id = "full-profile"
purpose = "Complete selective adaptive topology."
topology = "full"
comparison_class = "full_profile"
[[variants]]
id = "without-scout"
purpose = "Ablates native reconnaissance."
topology = "full_without_worker"
worker = "repo_scout"
comparison_class = "ablation"
[[variants]]
id = "without-implementation"
purpose = "Ablates the economical isolated implementation branch."
topology = "full_without_worker"
worker = "implementation_specialist"
comparison_class = "ablation"
[[variants]]
id = "without-review"
purpose = "Ablates independent cross-maker review."
topology = "full_without_worker"
worker = "adversarial_reviewer"
comparison_class = "ablation"
[[tasks]]
id = "decomposable-ledger"
description = "Repair an idempotency defect with separable reconnaissance, implementation, and review work."
sandbox = "workspace-write"
difficulty = "hard"
negative_control = false
wall_timeout_seconds = 2400
validation_timeout_seconds = 120
prompt = """
Repair the ledger defect described in SPEC.md. Own diagnosis and canonical integration. Delegate only work with a concrete expected contribution, continue non-overlapping critical-path work while it runs, explicitly accept or reject results, and end with EVAL_ADAPTIVE_VERIFIED.
"""
[tasks.outcome_assertions]
expected_patterns = ["EVAL_ADAPTIVE_VERIFIED"]
forbidden_patterns = []
validation_commands = ["python -m unittest -v"]
[tasks.orchestration_assertions]
required_agents = ["implementation_specialist", "adversarial_reviewer"]
max_jobs = 3
max_contract_failures = 0
max_observed_mcp_wait_ratio = 0.8
[[tasks]]
id = "tight-small-change"
description = "Negative control where worker launch overhead should not be required."
sandbox = "workspace-write"
difficulty = "easy"
negative_control = true
wall_timeout_seconds = 1200
validation_timeout_seconds = 120
prompt = """
Make the smallest correct ledger repair. This task is intentionally compact: remain single-agent unless independent work has a concrete positive expected value. Run the tests and end with EVAL_ADAPTIVE_SMALL.
"""
[tasks.outcome_assertions]
expected_patterns = ["EVAL_ADAPTIVE_SMALL"]
forbidden_patterns = []
validation_commands = ["python -m unittest -v"]
[tasks.orchestration_assertions]
max_jobs = 1
max_contract_failures = 0