gpt-instruct
A Codex jailbreak prompt and test pack for gpt. 针对 gpt 系列的 Codex 破甲提示词与测试包。
Runs with mockssource: GitHubhomepagePythonMITcommit 0ad8ec58e198
Python, MIT licensed.
gpt-instruct runs, with stand-ins for the services it depends on. An Argusic agent installed it in 1.2 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
All 26 unit tests and 47 scoring-verification tests pass, both prompt archives deploy correctly and match their published SHA256 hashes, script ZIPs all test valid, and standalone verification tools (candidate validator, self-test runner, safety eval dry-run) produce correct output.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 92 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
- Install time
- 1 minutes
- Cold machine to finish
- 5 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- How the result was proved
- python3 -m unittest discover -s unit-tests -q exited 0, 26/26 passed; python3 scripts/extracted/verify_gpt56_sol_regression_scoring.py exited 0, 47/47 passed; python3 scripts/extracted/run_gpt56_sol_issue_regression.py --self-test exited 0 with 'pass'; python3 codex-instruct.py --apply --version gpt-5.6-v45 deployed prompt to ~/.codex without errors; SHA256 hashes of ZIPs match README
- Model tokens used
- 206,465
- Exact commit tested
- 0ad8ec58e198
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
提示词状态 / Prompt status: 已移除 0 个，保留 0 个 / Removed 0, preserved 0 [data] deployed cache not found; using repository seed STDERR: [错误] 目标文件已存在且不属于本脚本，未覆盖: /tmp/tmp4r3zlbiy/custom-prompt.md [Error] Destination exists but is not owned by this script; choose another --name. [warning] Local Star History refresh failed; reusing the last deployed chart pair: local Star Histo… Ran 26 tests in 1.248s OK EXIT: 0 Here's the final report on the `gpt-instruct` repository. tokens used 206,465 Here's the final report on the `gpt-instruct` repository.
Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Installed in 1.2 minutes, faster than the median of the 13 comparable projects Argusic has measured.
- Nothing broke on the way: zero errors between clone and running.
- Licensed MIT, as reported by its host.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 14 Python projects Argusic has installed and timed, gpt-instruct was the 3rd fastest to reach a running state, and 8 of 14 reached one at all.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 1/3 | Runs with mocks | 92.00 | 0.05 |
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/gpt-instruct)Questions
- Does gpt-instruct run?
- gpt-instruct runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 1 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test gpt-instruct?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 0ad8ec58e198. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test gpt-instruct?
- The run that produced this verdict cost $0.05: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does gpt-instruct take to install?
- 1.2 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does gpt-instruct need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing gpt-instruct?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does gpt-instruct compare with the alternatives?
- Of the 14 Python projects Argusic has installed and timed, gpt-instruct was the 3rd fastest to reach a running state, and 8 of 14 reached one at all.
- Where is the evidence for gpt-instruct?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.