SyncVals · Trajectory

lru-cache

codex gpt-5.5 ✓ resolved GOOD_SUCCESS ↑ View task

Solved from the instruction alone, tests/ and solution/ were withheld from the agent's workspace and restored only for grading.

Reward = tests/test.sh exit code (0 → resolved); the classification below is post-hoc and cannot change it.

Classification , post-hoc; cannot change the reward

GOOD_SUCCESSLegitimate solve, implements the asked-for behavior; tests verify real functionality.

SubtypeLegitimate Solution - Complex Algorithm

EvidenceAgent implemented a complete segmented cache simulator that passes all 13 tests: test_output_exists, test_shipped_input_correct, test_shipped_exercises_the_gate, test_shipped_invariants, and test_hidden_inputs with 8 randomized seeds (seeds 3,4,8,11,13,16,33,47) plus test_hidden_inputs_are_nontrivial. The agent's SegmentedCache class correctly implements all required rules: logical clock expiry, frequency tracking with periodic halving, two-segment LRU promotion/demotion, weighted eviction, and frequency-gated admission. The reference implementation in the test suite (test_outputs.py::reference_sim) uses a structurally different representation but both produce identical results on all inputs. Final output matches reference exactly: get_results=[100, 200, 100, 300, 100, 200, -1, 400, 100, 200, -1, 800, -1], final_probation=[[2,200]], final_protected=[[1,150],[8,800]], total_weight=5, rejected=2.

Root causeThe agent demonstrated exceptional capability in understanding and implementing a complex, multi-rule cache simulation from detailed written specification alone. The solution passes comprehensive testing including anti-hardcoding hidden inputs, proving general correctness rather than memorization.

RecommendationN/A - task is fine

Trajectory

Tool-by-tool agent trajectory

20 tool calls · 2 tool types · 28 steps

I’ll inspect the trace shape and repo first, then implement the simulator in `main.py` and run it to produce `output/result.json`. After that I’ll sanity-check the output against the stated invariants.

shell

/bin/zsh -lc 'git status --short'

shell

/bin/zsh -lc 'git status --short'

output

fatal: not a git repository (or any of the parent directories): .git

shell

/bin/zsh -lc 'pwd && rg --files -n .'

shell

/bin/zsh -lc 'pwd && rg --files -n .'

output

<tmp>/workspace
./data/operations.json
./main.py
./task.toml
./environment/README.md
./instruction.md

The workspace is minimal: `data/operations.json` and an existing `main.py`; there is no git repo around it, so I’ll avoid any git-based assumptions. Next I’m reading the current implementation and the trace parameters so the simulator matches the actual input.

shell

/bin/zsh -lc "sed -n '1,240p' main.py"

shell

/bin/zsh -lc "sed -n '1,240p' main.py"

output

# Read data/operations.json and write output/result.json.
#
# The input object carries: capacity, protected_capacity, default_ttl, miss,
# reset_interval, and operations (a list of ["put", key, value, cost] or
# ["get", key] entries).
#
# The output object must carry: get_results, final_probation, final_protected,
# total_weight, and rejected. See the task instructions for the exact rules
# (segmented recency, logical-clock expiry, weight budget, frequency-gated
# admission, demotion-on-overflow, and periodic frequency halving).
#
# TODO: implement the cache. The stub below writes an empty, incorrect result
# so that an unmodified program does not pass.
import json
import os

with open("data/operations.json") as f:
    data = json.load(f)

capacity = data["capacity"]
operations = data["operations"]

result = {
    "get_results": [],
    "final_probation": [],
    "final_protected": [],
    "total_weight": 0,
    "rejected": 0,
}

os.makedirs("output", exist_ok=True)
with open("output/result.json", "w") as f:
    json.dump(result, f)

shell

/bin/zsh -lc "python3 - <<'PY'
import json
p='data/operations.json'
with open(p) as f: d=json.load(f)
print({k:d[k] for k in d if k"'!='"'operations'})
print('operations', len(d['operations']))
print('gets', sum(1 for op in d['operations'] if op[0]=='get'))
print('puts', sum(1 for op in d['operations'] if op[0]=='put'))
print('first10', d['operations'][:10])
print('last10', d['operations'][-10:])
PY"

shell

/bin/zsh -lc "python3 - <<'PY'
import json
p='data/operations.json'
with open(p) as f: d=json.load(f)
print({k:d[k] for k in d if k"'!='"'operations'})
print('operations', len(d['operations']))
print('gets', sum(1 for op in d['operations'] if op[0]=='get'))
print('puts', sum(1 for op in d['operations'] if op[0]=='put'))
print('first10', d['operations'][:10])
print('last10', d['operations'][-10:])
PY"

output

{'capacity': 9, 'protected_capacity': 4, 'default_ttl': 8, 'miss': -1, 'reset_interval': 7}
operations 22
gets 13
puts 9
first10 [['put', 1, 100, 2], ['put', 2, 200, 2], ['put', 3, 300, 1], ['get', 1], ['get', 2], ['get', 1], ['put', 4, 400, 2], ['get', 3], ['get', 1], ['put', 5, 500, 2]]
last10 [['put', 6, 600, 3], ['get', 4], ['put', 7, 700, 4], ['get', 1], ['get', 2], ['put', 8, 800, 1], ['get', 3], ['put', 1, 150, 2], ['get', 8], ['get', 77]]

shell

/bin/zsh -lc "python3 -m json.tool data/operations.json | sed -n '1,120p'"

shell

/bin/zsh -lc "python3 -m json.tool data/operations.json | sed -n '1,120p'"

output

{
    "capacity": 9,
    "protected_capacity": 4,
    "default_ttl": 8,
    "miss": -1,
    "reset_interval": 7,
    "operations": [
        [
            "put",
            1,
            100,
            2
        ],
        [
            "put",
            2,
            200,
            2
        ],
        [
            "put",
            3,
            300,
            1
        ],
        [
            "get",
            1
        ],
        [
            "get",
            2
        ],
        [
            "get",
            1
        ],
        [
            "put",
            4,
            400,
            2
        ],
        [
            "get",
            3
        ],
        [
            "get",
            1
        ],
        [
            "put",
            5,
            500,
            2
        ],
        [
            "get",
            2
        ],
        [
            "get",
            99
        ],
        [
            "put",
            6,
            600,
            3
        ],
        [
            "get",
            4
        ],
        [
            "put",
            7,
            700,
            4
        ],
        [
            "get",
            1
        ],
        [
            "get",
            2
        ],
        [
            "put",
            8,
            800,
            1
        ],
        [
            "get",
            3
        ],
        [
            "put",
            1,
            150,
            2
        ],
        [
            "get",
            8
        ],
        [
            "get",
            77
        ]
    ]
}

The trace is small, but the rules have enough edge cases that I’m going to implement the full general simulator rather than hand-compute this specific file. I’ll use ordered maps for the two segments so LRU/MRU moves and candidate walks are explicit.

I’m replacing the stub with a simulator that tracks expiry, persistent frequencies, probation/protected recency, promotion demotion, weighted eviction, and admission contests in the exact order described.

write · /var/folders/4w/8dz5qwsn6p79xjvgb6gwgs640000gn/T/eval-platform-local-6jgspqbb/workspace/main.py

(empty file)

write · /var/folders/4w/8dz5qwsn6p79xjvgb6gwgs640000gn/T/eval-platform-local-6jgspqbb/workspace/main.py

(empty file)

The simulator is in place. I’m running it now and then I’ll inspect the generated result and do a quick trace/invariant check.

shell

/bin/zsh -lc 'python3 -m py_compile main.py'

shell

/bin/zsh -lc 'python3 -m py_compile main.py'

shell

/bin/zsh -lc 'python3 main.py && python3 -m json.tool output/result.json'

shell

/bin/zsh -lc 'python3 main.py && python3 -m json.tool output/result.json'

output

{
    "get_results": [
        100,
        200,
        100,
        300,
        100,
        200,
        -1,
        400,
        100,
        200,
        -1,
        800,
        -1
    ],
    "final_probation": [
        [
            2,
            200
        ]
    ],
    "final_protected": [
        [
            1,
            150
        ],
        [
            8,
            800
        ]
    ],
    "total_weight": 5,
    "rejected": 2
}

`main.py` runs cleanly and creates `output/result.json`. I’m doing one more focused verification pass around expirations, promotions/demotions, and the two rejected admissions because those are the places this cache can be misread.

shell

/bin/zsh -lc "python3 - <<'PY'
import json
from main import SegmentedCache

with open('data/operations.json') as f:
    data=json.load(f)
cache=SegmentedCache(data['capacity'],data['protected_capacity'],data['default_ttl'],data['miss'],data['reset_interval'])
for i, op in enumerate(data['operations'], 1):
    before_rej = cache.rejected
    cache.process(op)
    p=[(k,e.value,e.cost,e.expiry,cache.freq[k]) for k,e in cache.probation.items()]
    q=[(k,e.value,e.cost,e.expiry,cache.freq[k]) for k,e in cache.protected.items()]
    note=' REJECTED' if cache.rejected>before_rej else ''
    print(i, op, 't=', cache.clock, 'prob=', p, 'prot=', q, 'weight=', cache.total_weight(), 'gets=', cache.get_results[-1:] if op[0]=='get' else '', 'freq=', dict(sorted(cache.freq.items())), note)
print('RESULT', cache.result())
PY"

shell

/bin/zsh -lc "python3 - <<'PY'
import json
from main import SegmentedCache

with open('data/operations.json') as f:
    data=json.load(f)
cache=SegmentedCache(data['capacity'],data['protected_capacity'],data['default_ttl'],data['miss'],data['reset_interval'])
for i, op in enumerate(data['operations'], 1):
    before_rej = cache.rejected
    cache.process(op)
    p=[(k,e.value,e.cost,e.expiry,cache.freq[k]) for k,e in cache.probation.items()]
    q=[(k,e.value,e.cost,e.expiry,cache.freq[k]) for k,e in cache.protected.items()]
    note=' REJECTED' if cache.rejected>before_rej else ''
    print(i, op, 't=', cache.clock, 'prob=', p, 'prot=', q, 'weight=', cache.total_weight(), 'gets=', cache.get_results[-1:] if op[0]=='get' else '', 'freq=', dict(sorted(cache.freq.items())), note)
print('RESULT', cache.result())
PY"

output

1 ['put', 1, 100, 2] t= 1 prob= [(1, 100, 2, 9, 1)] prot= [] weight= 2 gets=  freq= {1: 1} 
2 ['put', 2, 200, 2] t= 2 prob= [(1, 100, 2, 9, 1), (2, 200, 2, 10, 1)] prot= [] weight= 4 gets=  freq= {1: 1, 2: 1} 
3 ['put', 3, 300, 1] t= 3 prob= [(1, 100, 2, 9, 1), (2, 200, 2, 10, 1), (3, 300, 1, 11, 1)] prot= [] weight= 5 gets=  freq= {1: 1, 2: 1, 3: 1} 
4 ['get', 1] t= 4 prob= [(2, 200, 2, 10, 1), (3, 300, 1, 11, 1)] prot= [(1, 100, 2, 12, 2)] weight= 5 gets= [100] freq= {1: 2, 2: 1, 3: 1} 
5 ['get', 2] t= 5 prob= [(3, 300, 1, 11, 1)] prot= [(1, 100, 2, 12, 2), (2, 200, 2, 13, 2)] weight= 5 gets= [200] freq= {1: 2, 2: 2, 3: 1} 
6 ['get', 1] t= 6 prob= [(3, 300, 1, 11, 1)] prot= [(2, 200, 2, 13, 2), (1, 100, 2, 14, 3)] weight= 5 gets= [100] freq= {1: 3, 2: 2, 3: 1} 
7 ['put', 4, 400, 2] t= 7 prob= [(3, 300, 1, 11, 0), (4, 400, 2, 15, 0)] prot= [(2, 200, 2, 13, 1), (1, 100, 2, 14, 1)] weight= 7 gets=  freq= {1: 1, 2: 1, 3: 0, 4: 0} 
8 ['get', 3] t= 8 prob= [(4, 400, 2, 15, 0), (2, 200, 2, 13, 1)] prot= [(1, 100, 2, 14, 1), (3, 300, 1, 16, 1)] weight= 7 gets= [300] freq= {1: 1, 2: 1, 3: 1, 4: 0} 
9 ['get', 1] t= 9 prob= [(4, 400, 2, 15, 0), (2, 200, 2, 13, 1)] prot= [(3, 300, 1, 16, 1), (1, 100, 2, 17, 2)] weight= 7 gets= [100] freq= {1: 2, 2: 1, 3: 1, 4: 0} 
10 ['put', 5, 500, 2] t= 10 prob= [(4, 400, 2, 15, 0), (2, 200, 2, 13, 1), (5, 500, 2, 18, 1)] prot= [(3, 300, 1, 16, 1), (1, 100, 2, 17, 2)] weight= 9 gets=  freq= {1: 2, 2: 1, 3: 1, 4: 0, 5: 1} 
11 ['get', 2] t= 11 prob= [(4, 400, 2, 15, 0), (5, 500, 2, 18, 1), (3, 300, 1, 16, 1)] prot= [(1, 100, 2, 17, 2), (2, 200, 2, 19, 2)] weight= 9 gets= [200] freq= {1: 2, 2: 2, 3: 1, 4: 0, 5: 1} 
12 ['get', 99] t= 12 prob= [(4, 400, 2, 15, 0), (5, 500, 2, 18, 1), (3, 300, 1, 16, 1)] prot= [(1, 100, 2, 17, 2), (2, 200, 2, 19, 2)] weight= 9 gets= [-1] freq= {1: 2, 2: 2, 3: 1, 4: 0, 5: 1, 99: 1} 
13 ['put', 6, 600, 3] t= 13 prob= [(4, 400, 2, 15, 0), (5, 500, 2, 18, 1), (3, 300, 1, 16, 1)] prot= [(1, 100, 2, 17, 2), (2, 200, 2,
… (+2084 chars truncated)

The verification pass matches the generated file: the two rejections happen on admissions for keys `6` and `7`, and the final expiry sweep at clock `22` removes key `4`. I’m checking the output file one last time for schema and expected key count.

shell

/bin/zsh -lc "python3 - <<'PY'
import json, os
with open('output/result.json') as f:
    result=json.load(f)
assert list(result.keys()) == ['get_results','final_probation','final_protected','total_weight','rejected']
assert len(result['get_results']) == 13
assert result['total_weight'] == 5
assert os.path.exists('output/result.json')
print('ok')
PY"

shell

/bin/zsh -lc "python3 - <<'PY'
import json, os
with open('output/result.json') as f:
    result=json.load(f)
assert list(result.keys()) == ['get_results','final_probation','final_protected','total_weight','rejected']
assert len(result['get_results']) == 13
assert result['total_weight'] == 5
assert os.path.exists('output/result.json')
print('ok')
PY"

output

ok

Implemented the simulator in [main.py](<tmp>/workspace/main.py) and generated [output/result.json](<tmp>/workspace/output/result.json). Result: ```json { "get_results": [100, 200, 100, 300, 100, 200, -1, 400, 100, 200, -1, 800, -1], "final_probation": [[2, 200]], "final_protected": [[1, 150], [8, 800]], "total_weight": 5, "rejected": 2 } ``` Verified with `python3 main.py`, `python3 -m py_compile main.py`, and a schema check on the generated JSON.

Final diff , what the agent changed

--- a/main.py

+++ b/main.py

@@ -1,33 +1,188 @@

-# Read data/operations.json and write output/result.json.

-# The input object carries: capacity, protected_capacity, default_ttl, miss,

-# reset_interval, and operations (a list of ["put", key, value, cost] or

-# ["get", key] entries).

-# The output object must carry: get_results, final_probation, final_protected,

-# total_weight, and rejected. See the task instructions for the exact rules

-# (segmented recency, logical-clock expiry, weight budget, frequency-gated

-# admission, demotion-on-overflow, and periodic frequency halving).

-# TODO: implement the cache. The stub below writes an empty, incorrect result

-# so that an unmodified program does not pass.

import json

import os

+from collections import OrderedDict, defaultdict

+from dataclasses import dataclass

-with open("data/operations.json") as f:

- data = json.load(f)

-capacity = data["capacity"]

-operations = data["operations"]

+@dataclass

+class Entry:

+ value: int

+ cost: int

+ expiry: int

-result = {

- "get_results": [],

- "final_probation": [],

- "final_protected": [],

- "total_weight": 0,

- "rejected": 0,

-os.makedirs("output", exist_ok=True)

-with open("output/result.json", "w") as f:

- json.dump(result, f)

+class SegmentedCache:

+ def __init__(self, capacity, protected_capacity, default_ttl, miss, reset_interval):

+ self.capacity = capacity

+ self.protected_capacity = protected_capacity

+ self.default_ttl = default_ttl

+ self.miss = miss

+ self.reset_interval = reset_interval

+ self.clock = 0

+ self.processed = 0

+ self.freq = defaultdict(int)

+ self.probation = OrderedDict()

+ self.protected = OrderedDict()

+ self.get_results = []

+ self.rejected = 0

+ def total_weight(self):

+ return self.segment_weight(self.probation) + self.segment_weight(self.protected)

+ @staticmethod

+ def segment_weight(segment):

+ return sum(entry.cost for entry in segment.values())

+ def process(self, operation):

+ self.clock += 1

+ self.sweep_expired()

+ op = operation[0]

+ key = operation[1]

+ self.freq[key] += 1

+ if op == "get":

+ self.get(key)

+ elif op == "put":

+ _, _, value, cost = operation

+ self.put(key, value, cost)

+ else:

+ raise ValueError(f"unknown operation: {op}")

+ self.processed += 1

+ if self.processed % self.reset_interval == 0:

+ self.age_frequencies()

+ def sweep_expired(self):

+ for segment in (self.probation, self.protected):

+ expired = [key for key, entry in segment.items() if entry.expiry <= self.clock]

+ for key in expired:

+ del segment[key]

+ def age_frequencies(self):

+ for key in list(self.freq):

+ self.freq[key] //= 2

+ def get(self, key):

+ if key in self.protected:

+ entry = self.protected[key]

+ entry.expiry = self.clock + self.default_ttl

+ self.protected.move_to_end(key)

+ self.get_results.append(entry.value)

+ return

+ if key in self.probation:

+ entry = self.probation.pop(key)

+ entry.expiry = self.clock + self.default_ttl

+ self.protected[key] = entry

+ self.get_results.append(entry.value)

+ self.demote_until_protected_fits()

+ return

+ self.get_results.append(self.miss)

+ def demote_until_protected_fits(self):

+ while self.segment_weight(self.protected) > self.protected_capacity:

+ key, entry = self.protected.popitem(last=False)

+ self.probation[key] = entry

+ def put(self, key, value, cost):

+ if key in self.probation:

+ entry = self.probation[key]

+ entry.value = value

+ entry.cost = cost

+ entry.expiry = self.clock + self.default_ttl

+ self.probation.move_to_end(key)

+ self.evict_until_total_fits(skip_key=key)

+ return

+ if key in self.protected:

+ entry = self.protected[key]

+ entry.value = value

+ entry.cost = cost

+ entry.expiry = self.clock + self.default_ttl

+ self.protected.move_to_end(key)

+ self.evict_until_total_fits(skip_key=key)

+ return

+ self.admit_new(key, value, cost)

+ def evict_until_total_fits(self, skip_key):

+ while self.total_weight() > self.capacity:

+ victim = self.find_eviction_victim(skip_key)

+ if victim is None:

+ break

+ segment, key = victim

+ del segment[key]

+ def find_eviction_victim(self, skip_key):

+ for segment in (self.probation, self.protected):

+ for key in segment:

+ if key != skip_key:

+ return segment, key

+ return None

+ def admit_new(self, key, value, cost):

+ if cost > self.capacity:

+ self.rejected += 1

+ return

+ needed = self.total_weight() + cost - self.capacity

+ victims = []

+ freed = 0

+ if needed > 0:

+ for segment in (self.probation, self.protected):

+ for resident_key, entry in segment.items():

+ victims.append((segment, resident_key))

+ freed += entry.cost

+ if self.freq[key] <= self.freq[resident_key]:

+ self.rejected += 1

+ return

+ if freed >= needed:

+ break

+ if freed >= needed:

+ break

+ for segment, resident_key in victims:

+ del segment[resident_key]

+ self.probation[key] = Entry(

+ value=value,

+ cost=cost,

+ expiry=self.clock + self.default_ttl,

+ )

+ def result(self):

+ return {

+ "get_results": self.get_results,

+ "final_probation": [[key, entry.value] for key, entry in self.probation.items()],

+ "final_protected": [[key, entry.value] for key, entry in self.protected.items()],

+ "total_weight": self.total_weight(),

+ "rejected": self.rejected,

+ }

+def main():

+ with open("data/operations.json") as f:

+ data = json.load(f)

+ cache = SegmentedCache(

+ capacity=data["capacity"],

+ protected_capacity=data["protected_capacity"],

+ default_ttl=data["default_ttl"],

+ miss=data["miss"],

+ reset_interval=data["reset_interval"],

+ )

+ for operation in data["operations"]:

+ cache.process(operation)

+ os.makedirs("output", exist_ok=True)

+ with open("output/result.json", "w") as f:

+ json.dump(cache.result(), f)

+if __name__ == "__main__":

+ main()

--- /dev/null

+++ b/output/result.json

@@ -0,0 +1 @@

+{"get_results": [100, 200, 100, 300, 100, 200, -1, 400, 100, 200, -1, 800, -1], "final_probation": [[2, 200]], "final_protected": [[1, 150], [8, 800]], "total_weight": 5, "rejected": 2}

Verifier output , the proof behind the reward

tests/test.sh

============================= test session starts ==============================
platform darwin -- Python 3.12.4, pytest-8.4.1, pluggy-1.6.0 -- /Library/Frameworks/Python.framework/Versions/3.12/bin/python3
cachedir: .pytest_cache
rootdir: <tmp>/workspace
plugins: anyio-4.12.1, respx-0.22.0, mock-3.15.1, asyncio-0.21.1
asyncio: mode=Mode.STRICT
collecting ... collected 13 items

tests/test_outputs.py::test_output_exists PASSED                         [  7%]
tests/test_outputs.py::test_shipped_input_correct PASSED                 [ 15%]
tests/test_outputs.py::test_shipped_exercises_the_gate PASSED            [ 23%]
tests/test_outputs.py::test_shipped_invariants PASSED                    [ 30%]
tests/test_outputs.py::test_hidden_inputs[3] PASSED                      [ 38%]
tests/test_outputs.py::test_hidden_inputs[4] PASSED                      [ 46%]
tests/test_outputs.py::test_hidden_inputs[8] PASSED                      [ 53%]
tests/test_outputs.py::test_hidden_inputs[11] PASSED                     [ 61%]
tests/test_outputs.py::test_hidden_inputs[13] PASSED                     [ 69%]
tests/test_outputs.py::test_hidden_inputs[16] PASSED                     [ 76%]
tests/test_outputs.py::test_hidden_inputs[33] PASSED                     [ 84%]
tests/test_outputs.py::test_hidden_inputs[47] PASSED                     [ 92%]
tests/test_outputs.py::test_hidden_inputs_are_nontrivial PASSED          [100%]

============================== 13 passed in 0.27s ==============================

Reproduce this trial: git checkout 2f94510 && PYTHONPATH=src python3 scripts/build_site.py , then open trial/trial_db43abb9785a4f73. Re-running the agent live requires EVAL_PLATFORM_ENABLE_OAUTH_SMOKE=1 and is non-deterministic.

Trial trial_db43abb9785a4f73 · verifier authoritative; classifier explanatory.