Experiment 6.2: Codex as the human benchmark operator¶
This document records one easy, one medium, and one hard case from each of the six benchmark families named by Experiment 6.2. Codex personally operated every case. These are Codex's trajectories, not work performed by the repository owner or user.
The final result is 13/18 passed (72.2%). All 18 selected cases reached one terminal official result; five first-attempt failures are retained without repair or score-seeking reruns.
Methodology¶
Task selection was locked before solving and before inspecting gold answers or reference patches. The preregistration is selection_manifest.json, committed separately before execution. Its SHA-256 is 0fa3f6f890e69c0e51db6ea50d46186af999c5ad0a24284055bbebd667fa15b7.
The rules for every case were:
- Use the task and tier fixed in the selection manifest; do not replace a hard or failed case with a more favorable one.
- Act as the human operator: reason about the task, invoke the environment's normal tools, and create the requested answer, patch, or artifact directly.
- Do not inspect a gold answer, reference solution, or evaluator-specific expected artifact before freezing the answer or work product.
- Invoke the upstream official evaluator once and preserve its first terminal result.
- Explain evaluator failures from the retained evidence, but do not revise and resubmit a failed case.
GAIA's upstream Levels 1/2/3 supply its difficulty tiers. AndroidWorld and Terminal-Bench use upstream difficulty labels. SWE-bench Verified uses the upstream human-time buckets <15 min, 15 min - 1 hour, and >4 hours. τ²-bench uses two, three, and nine composed telecom faults. OSWorld-Verified has no difficulty field, so the preregistered operational proxies are one persistent setting in one application, one structured transformation in one application, and a cross-application artifact transformation.
results.json is the machine-readable 18-case index. The files below are the canonical per-step records:
runs/gaia/operator_answers.jsonruns/androidworld/results.jsonruns/swe-bench-verified/results.jsonruns/tau2-bench/results.jsonruns/terminal-bench/results.jsonruns/osworld-verified/results.json
The τ² results directory also retains three exact benchmark transcripts, and the OSWorld directory retains the exact submitted pyautogui action logs. Large screenshots, benchmark images, containers, and source checkouts are intentionally excluded.
Results at a glance¶
| Benchmark | Easy | Medium | Hard | Total |
|---|---|---|---|---|
| GAIA | Pass | Fail | Pass | 2/3 |
| AndroidWorld | Pass | Pass | Fail | 2/3 |
| SWE-bench Verified | Pass | Pass | Fail | 2/3 |
| τ²-bench | Pass | Pass | Fail | 2/3 |
| Terminal-Bench | Pass | Pass | Fail | 2/3 |
| OSWorld-Verified | Pass | Pass | Pass | 3/3 |
| Overall | 6/6 | 5/6 | 2/6 | 13/18 |
This tiny, deliberately stratified sample is a hands-on methodology exercise, not a benchmark leaderboard claim. In particular, the near-monotonic aggregate decline from easy to hard is descriptive only.
Compatibility boundaries¶
- AndroidWorld: the reference gRPC accessibility feed/forwarder failed in this server environment. The runs retained upstream
HumanAgent, task initialization, deterministic parameters, and official evaluators, but used AndroidWorld's upstreamUIAUTOMATORcontroller for observation. - τ²-bench: no valid hosted-model credential was available for the benchmark's hidden user role. OpenAI credentials were absent and the available Anthropic credential returned HTTP 401. A locally cached
Qwen/Qwen2.5-3B-Instructran the standard hidden user scenario on CPU. Codex remained the support-agent operator. The simulator's role inversion is part of the hard-case failure, so results from this compatibility path must not be presented as reference-provider-comparable. - OSWorld-Verified: the upstream Docker/KVM image was used with
/dev/kvm. All computer interaction was performed through visiblepyautoguiactions. Full-resolution screenshots were retained during execution but omitted from Git; the exact submitted actions and first official scores are preserved. - SWE-bench Verified: local setup failures were used only for diagnosis. The frozen patches were scored by the official containerized evaluation harness under run ID
exp6-2-human-20260803.
GAIA¶
Source commit: 682dd723ee1e1697e00360edccf2366dc8418dd9.
Easy — 2d83110e-a098-4ebb-9987-066c06fa42d0 — Pass¶
What the task was about. Interpret a sentence written backward and answer with the opposite of the word left.
Trajectory. I read the string from right to left, recovered the instruction “If you understand this sentence, write the opposite of the word left as the answer,” mapped left to its directional opposite, and froze the answer right.
Evaluation. The stored validation answer was right, so the exact-answer checker awarded 1.0. The task succeeded because both decoding and antonym selection were exact.
Medium — 7dd30055-0198-452e-8c25-f73dbe27dcb8 — Fail¶
What the task was about. Parse an attached PDB structure with Biopython, measure the distance between its first two listed atoms, and report the result rounded to the nearest picometer.
Trajectory. I fetched only the selected 2,897,289-byte LFS attachment. Creating an isolated Python environment initially failed because ensurepip/python3.10-venv was missing, so I installed that system package, created /home/ubuntu/.venvs/exp6-2-gaia-v2, and installed Biopython 1.85. Bio.PDB.PDBParser(QUIET=True) identified atom N followed by atom CA in chain A, residue 2. Biopython returned 1.4564234018325806 Å. Because 1 pm is 0.01 Å, I rounded to 1.46 Å and froze that answer.
Evaluation. The official stored answer was numeric 1.456, and the reference checker compared it exactly rather than accepting the prompt-requested nearest-picometer rounding. It awarded 0.0. This is recorded as a failure: 1.46 followed the stated rounding instruction, but it did not satisfy the actual checker. I did not replace it with the gold value after evaluation.
Hard — 56db2318-640f-477a-a82f-bc93ad13e882 — Pass¶
What the task was about. Infer an unknown alternating checksum weight and an adjacent transposed column from ten ISBN-like records.
Trajectory. I removed hyphens and converted every 13-digit row to integers. I enumerated alternate weights 2 through 9 and allowed adjacent swaps whose smaller index was 3 through 10, excluding the fixed prefix and checksum digit. For every candidate I applied weights 1,w,1,w,... across all 13 digits and required every row's weighted sum modulo 10 to be zero. Exactly one candidate survived: (7, 9). I froze 7, 9.
Evaluation. The answer exactly matched the stored validation answer, yielding 1.0.
AndroidWorld¶
Source commit: 0e95d641e244504c22087cc29b013f3b2428a261. Suite seeds were 6201, 6202, and 6203.
Easy — ContactsAddContact — Pass¶
What the task was about. Create a contact named Samuel Ali with phone number +16237655787.
Trajectory. I opened Contacts from the launcher, completed its first-run screen, chose Create new contact, entered Samuel and Ali in the name fields, entered the international number, saved, and observed the Samuel Ali detail page showing the formatted number 1 (623) 765-5787.
Evaluation. The upstream state evaluator found the requested name and phone number in the contacts database and awarded 1.0. Display punctuation did not alter the stored digits.
Medium — CameraTakeVideo — Pass¶
What the task was about. Use the system Camera application to create one video.
Trajectory. I opened Camera, switched from still-photo mode to Video, pressed record, allowed about three seconds of capture, pressed stop, and left the created media artifact in device storage.
Evaluation. The official media-state evaluator found one newly created video and awarded 1.0.
Hard — BrowserMultiply — Fail¶
What the task was about. Open task.html from Downloads in Chrome, reveal a deterministic five-number sequence, remember it, and submit the product.
Trajectory. I opened Files, navigated to Downloads, selected task.html, chose Chrome, and completed Chrome's first-run prompts. I observed the initial 4, then clicked the page button five times. The subsequent displayed values were 2, 5, 3, and 7; the fifth press revealed the answer form. I computed 4 × 2 × 5 × 3 × 7 = 840, attempted to enter and submit 840, and froze the browser state.
Evaluation. The official evaluator did not observe the page text Success!, so it awarded 0.0. A post-evaluation replay of the pinned page's seeded RNG confirmed [4, 2, 5, 3, 7] and product 840; therefore the reasoning was correct, but the final form interaction did not reach the required UI state. The retained evidence cannot distinguish an unfocused field, unregistered submit tap, or another transient UI mismatch. I did not rerun it.
SWE-bench Verified¶
Source commit: 5cd4be9fb23971679cbbafe5a0ecade27cef99be. Official run ID: exp6-2-human-20260803; 3 submitted, 2 resolved, 1 unresolved, 0 harness errors.
Easy — django__django-11133 — Pass¶
What the task was about. Make Django's HttpResponse preserve the bytes represented by a memoryview instead of serializing the object's representation.
Trajectory. I traced HttpResponseBase.make_bytes and the HttpResponse.content setter. make_bytes treated bytes atomically, but the setter classified memoryview as a generic iterable. I changed make_bytes to use bytes(value) for bytes or memoryview, excluded memoryview from the setter's iterable path, and added constructor and property-assignment regressions. After installing missing sqlparse and pytz, all 12 local HttpResponseTests passed. I froze and submitted the patch once.
Evaluation. The official fail-to-pass test passed, as did all 64 pass-to-pass tests. The case resolved because both byte conversion and iterable dispatch were corrected.
Medium — astropy__astropy-13033 — Pass¶
What the task was about. Make TimeSeries required-column errors show the complete expected and observed prefixes when multiple columns are mandatory.
Trajectory. I read the issue, hint, and checker in astropy/timeseries/core.py. I preserved the established scalar wording when only one column is required. For multiple columns, I formatted the entire required list and the observed prefix of equal maximum length, then added the reported time/flux removal regression with the exact message. The old local checkout could not build its compiled/version stack, so I treated that as setup evidence rather than a product test result. I froze and submitted the patch once.
Evaluation. The official reported-issue test and all 20 pass-to-pass groups passed, resolving the case.
Hard — sphinx-doc__sphinx-7590 — Fail¶
What the task was about. Teach Sphinx's C++ expression parser to handle numeric user-defined literal suffixes such as q_J and q_s.
Trajectory. I reproduced the path where the float token was consumed but its adjacent suffix remained and triggered “Expected end of definition.” I added a suffix regex without a leading word boundary, consumed the suffix into ASTNumberLiteral, and added decimal and integer UDL tests. After resolving setup-only Jinja and roman dependency failures, the complete local C++ expression-parser test passed, including the reported Planck constant declaration. I froze and submitted once.
Evaluation. The patch recognized and rendered numeric UDLs, and all 24 official pass-to-pass groups passed. The hidden fail-to-pass test additionally required an Itanium ABI expression ID representing a call to the literal operator. My patch generated IE1CIAL5_udlE_1aE; the expected ID was IE1CIAclL_Zli4_udlEL5EE_1aE. The unresolved ABI identity defect made the official result 0.0; I did not revise or resubmit it.
τ²-bench¶
Source commit: 8d005b0e5b9e4af0bc055886fa7f95fc86d1710e. The support-agent trajectory was authored manually by Codex. The locally cached Qwen model supplied the benchmark's hidden user role under the compatibility boundary above.
Easy — two faults — Pass¶
Task ID: [mobile_data_issue]data_mode_off|data_usage_exceeded[PERSONA:None].
What the task was about. Restore mobile data after it had been turned off and its allowance exhausted, including correct paid-refuel consent.
Trajectory. I identified customer C1001 and affected line L1002, requested network diagnostics, directed the user to enable mobile data, and asked for a speed test. When it still failed, I inspected usage and plan P1002, finding 15.1 GB used against 15.0 GB and a $2/GB refuel. I offered up to 2 GB, explicitly confirmed the $4 total, called refuel_data only after consent, and requested a final test. The result was 275 Mbps (Excellent), after which I summarized the $4 charge and ended the interaction.
Evaluation. Official reward 1.0: mobile data was enabled, 2 GB was added with confirmation, and the final connection was Excellent.
Medium — three faults — Pass¶
Task ID: [mobile_data_issue]bad_vpn|data_saver_mode_on|user_abroad_roaming_disabled_on[PERSONA:None].
What the task was about. Repair poor data abroad caused by carrier-side roaming being off, Data Saver being on, and a degraded VPN.
Trajectory. I looked up the customer, mistakenly called nonexistent get_line_by_id, preserved the tool error, and recovered with get_details_by_id. I identified L1002, established that the user was abroad, and enabled carrier-side roaming. I followed the slow-data workflow: requested restriction status, directed Data Saver off, checked VPN performance before changing it, then directed the degraded OpenVPN connection to disconnect. The final speed test reported 275 Mbps (Excellent).
Evaluation. Official reward 1.0. The three required action checks—enable_roaming, toggle_data_saver_mode, and disconnect_vpn—all passed, as did the final environment assertion. The early invalid tool call changed no state and was correctly recovered.
Hard — nine faults — Fail¶
Task ID: [mms_issue]airplane_mode_on|bad_network_preference|bad_wifi_calling|break_apn_mms_setting|break_app_sms_permission|data_mode_off|data_usage_exceeded|unseat_sim_card|user_abroad_roaming_disabled_on[PERSONA:None].
What the task was about. Repair an MMS failure containing nine independent faults across radio state, SIM, roaming, data, allowance, network mode, Wi-Fi Calling, application permissions, and APN settings.
Trajectory. I established the affected line and baseline MMS failure; diagnosed and disabled airplane mode; diagnosed and reseated the SIM; enabled carrier-side roaming; enabled mobile data; diagnosed the exhausted allowance; confirmed and applied a 2 GB refuel for $4; changed the preferred network from 2G to 4g_5g_preferred; disabled Wi-Fi Calling; granted the Messaging app's missing SMS permission; identified the missing MMSC URL; reset APN settings and rebooted. The terminal checks showed that MMS could be sent and the data speed was 275 Mbps (Excellent).
The trajectory also records repeated recovery from user-simulator role inversion. Qwen frequently told the support agent to execute phone-side tools instead of executing them as the user. Near the step limit I explicitly requested multiple ordered phone calls in a single response. The exact operator turns are retained in runs/tau2-bench/hard-transcript.json.
Evaluation. Official reward 0.0. Although the final environment state was repaired, the episode hit the benchmark's 100-step cap before a recognized terminal stop. The official evaluator classified it as prematurely terminated and did not score the repaired state. This is an episode-level failure caused by the local user-model compatibility path, not a claim of benchmark success; I did not rerun it.
Terminal-Bench¶
Source commit: 8384a179b1b8688f6ea5233a4d9d51218df1ac96.
Easy — fix-permissions — Pass¶
What the task was about. Diagnose why /app/process_data.sh could not execute and repair it.
Trajectory. I listed /app, read the public script, and observed mode 664 (-rw-rw-r--). Running it produced Permission denied and exit 126. I ran chmod +x, confirmed mode 775, ran the script successfully, observed Data processed successfully!, and invoked the upstream test script.
Evaluation. The single official test test_script_permissions passed. Missing execute bits were the complete defect.
Medium — simple-sheets-put — Pass¶
What the task was about. Populate a stateful spreadsheet REST service while creating exactly one spreadsheet.
Trajectory. I queried /spreadsheets/ and confirmed zero initial objects, then used /docs/json to map spreadsheet, sheet, individual-cell, and batch-cell endpoints. I created one Financial Report spreadsheet and one Q1 Data sheet. The advertised batch-cell PUT returned HTTP 400 without mutation, so I used the documented individual-cell PUT for A1:D4. I entered the four headers, January–March rows, and profits 2000, 3000, and 5000. A final GET confirmed one spreadsheet and all 16 cells before evaluation.
Evaluation. All three official tests—spreadsheet, sheet, and cell creation—passed. The fallback preserved the singleton constraint and completed every value.
Hard — dna-assembly — Fail¶
What the task was about. Design the minimum Golden Gate primer set that assembles a backbone, EGFP, FLAG linker, and SNAP into an exact circular target plasmid while satisfying primer constraints.
Trajectory. I parsed five FASTA records, confirmed no internal BsaI sites, aligned the target, and inferred the intended component boundaries. I selected four primer pairs with junction overhangs ATGA, GGTA, GACA, and TAAT. Simulating the four digested fragments produced the exact 3,591-nt circular target up to rotation. I installed primer3, chose annealing tracts with the required thermodynamic parameters, wrote eight nonblank FASTA records, and invoked the official evaluator once.
Evaluation. test_primers failed. The FLAG forward overhang's four-base suffix also matched the adjacent template, so the evaluator correctly included it in the annealing tract. That primer's evaluated Tm was 66.056662°C, versus 60.610114°C for FLAG reverse—a 5.446548°C gap, exceeding the at-most-5°C constraint. My pre-evaluation check measured only the explicit 15-base binding suffix. The assembly itself was exact, but the primer-pair thermodynamic constraint made the official result a failure; no post-evaluation revision was made.
OSWorld-Verified¶
Source commit: 8365edc975efd0477a0d62444a5beed562ab5a7b. Each artifact was frozen before its official evaluator ran.
Easy — 2cd43775-7085-45d8-89fa-9e35c0a915cf — Pass¶
What the task was about. Enable LibreOffice AutoRecovery every three minutes.
Trajectory. I opened LibreOffice Options with Alt+F12, expanded Load/Save, opened General, enabled Save AutoRecovery information every, changed the interval from 10 to 3, committed the dialog, reopened it to visually verify persistence, and closed it without further mutation.
Evaluation. Official result 1. The evaluator found AutoRecovery enabled with a three-minute interval.
Medium — 7e429b8d-a3f0-4ed0-9b58-08957d00b127 — Pass¶
What the task was about. Fill officer names in a Calc table by matching each row's branch to a lookup table.
Trajectory. I entered =VLOOKUP(E2;$A$2:$B$7;2;0) in F2, selected F2:F12, filled down with Ctrl+D, visually checked the resulting names, and saved the workbook in place.
Evaluation. Official result 1.0. The artifact evaluator found every officer name correctly matched to its headoffice.
Hard — 51f5801c-18b3-4f25-b0c3-02f85507a078 — Pass¶
What the task was about. Extract every presenter note from Dickinson_Slides.pptx, write only the note text into an unformatted Word document, and save it as Desktop/notes.docx.
Trajectory. I switched Impress to Notes view and visited slides 1 through 9 in order. I transcribed: This is opening slide., Cover slide option #1, Cover slide option #3, This is a graph., This is a table., This is item lists., This is an inserted image., and Blank ending slide. Slide 7 contained only the empty “Click to add Notes” placeholder, so I omitted it. I opened Writer from the visible launcher, entered the eight texts as plain paragraphs with no labels or page numbers, opened Save As, selected Desktop, chose Word 2007–365 format, named the file notes.docx, and visually verified the filename and content before freezing.
Evaluation. Official result 1. The evaluator accepted the document, ordering, omission of the empty placeholder, location, filename, and lack of added formatting.
Interpretation¶
The five failures expose five different boundaries:
- Answer normalization: GAIA medium's requested rounding disagreed with the strict stored numeric value.
- Last-mile UI state: AndroidWorld hard had correct arithmetic but did not reach the page's visible success state.
- Hidden semantic contract: SWE-bench hard handled syntax but missed the ABI call identity required by the official test.
- Constraint verification: Terminal-Bench hard assembled the exact product but misidentified the full annealing tract for one primer.
- Episode protocol: τ²-bench hard repaired the environment but exhausted the turn budget under a role-inverting local user simulator.
That diversity is the main value of the exercise: “the answer looked right” is weaker than an official terminal result, and failures often occur at normalization, interaction, representation, secondary constraints, or protocol termination rather than at the apparent core task.