Datasets:
task_id stringlengths 6 11 | domain stringclasses 7
values | prompt stringlengths 365 3.71k |
|---|---|---|
finance-18 | finance | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Set up a discount curve and value a set of instruments. The file quotes.csv contains the columns ty... |
math-1 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Answer every exact-integer problem listed below. Because the values are too large for a naive brute... |
media-12 | media | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
stream.mcf is a corrupted media container. Its structure consists of the magic bytes 'MCF1' followe... |
office-3 | office | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The team roster is located in roster.csv (columns: full_name, aliases separated by pipes), and meet... |
science-12 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Combine the chemical kinetics model found in params.json (containing rate constants k1,k2,k3) with ... |
security-21 | security | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Audit a synthetic firewall ruleset. The file rules.csv has columns id,action,proto,src,dst,dport,en... |
software-17 | software | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Create `kv.py` (stub) containing `TxError(Exception)` and a `Store` class implementing an in-memory... |
finance-21 | finance | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Determine the contents of credit-card statements. The file transactions.csv contains the columns da... |
math-3 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Resolve the following computational problems precisely (python3 and numpy are available; Python int... |
media-13 | media | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file stream.mcf is a corrupted media container. Its structure begins with the magic bytes 'MCF1... |
office-14 | office | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Perform intercompany ledger reconciliation for the corporate group with a cutoff of 2026-09-30. ent... |
science-13 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Using the 4-species kinetics defined in params.json (k1,k2,k3,kf,kr, dose, t_dose), begin integrati... |
security-29 | security | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Read the verification spec for a webhook receiver located at SPEC.md in this directory. Then classi... |
software-23 | software | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Create `cronlib.py` (stub): define `next_times(expr, after, count) -> list[str]`, which acts as a c... |
finance-24 | finance | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file TICKET.md located in the current directory contains the month-end close request from the c... |
math-7 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file roads.csv contains a road network where lines beginning with # are comments, and if a pair... |
media-19 | media | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
playlist.m3u8 is a synthetic HLS media playlist. Determine its timeline structure. The rules are as... |
office-15 | office | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Perform reconciliation of the intercompany ledgers for a corporate group with a cutoff date of 2026... |
science-16 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file dist.csv contains a symmetric 13x13 matrix of estimated pairwise evolutionary distances, w... |
software-27 | software | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Create `interp.py` (stub) defining `InterpError(Exception)` and `interpolate(text, env) -> str`, wh... |
finance-25 | finance | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
In the current directory, TICKET.md contains the month-end close request from the controller. Read ... |
math-14 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The alphabet consists of {a,b,c}. The file params.json specifies the queries (lengths n) and the fo... |
media-24 | media | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Inside the same directory are the raw transcript, the referenced session data, and request.txt, a n... |
office-17 | office | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Create a 14-day schedule commencing on Monday 2026-11-02 (weeks run Mon-Sun, meaning days 1-7 and 8... |
science-20 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Identify the earthquake source using the provided phase picks. The file stations.csv provides colum... |
software-29 | software | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
In production, the `stockroom/` package is malfunctioning. The ticket and background information ar... |
finance-27 | finance | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Locate the file TICKET.md in the current directory, which contains a request from financial reporti... |
math-17 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Facility location problem. The file depots.csv has columns (id,fixed,cap); activating a depot incur... |
media-28 | media | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file request.txt contains a note from the podcast producer. The CMS export, site data, and uplo... |
office-22 | office | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
sheet.csv is a compact spreadsheet consisting of 5 columns (A to E) and 9 rows without a header: li... |
science-22 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file request.txt contains a colleague's note, while the remaining folder contents are outputs f... |
software-30 | software | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
README.md contains a ticket describing bugs in `migrate.py`, which loads a legacy CRM export into a... |
math-27 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
A ticket from the ops desk is stored in ticket.txt, located alongside the referenced exports. Follo... |
office-23 | office | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file sheet.csv is a compact spreadsheet consisting of 12 rows and 5 columns (A through E) witho... |
science-23 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file request.txt contains a note from a colleague; the remaining items in the folder are output... |
software-32 | software | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Read the README.md file, which describes a flaky scheduled job and directs you to its logs, then ge... |
math-28 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
ticket.txt requests specific numerical values regarding a customer promotion, and campaign_spec.md ... |
science-24 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
ticket.txt contains a request from a colleague, and the limits table, the flow log, and the lab exp... |
software-33 | software | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
The file README.md contains a ticket describing a flaky scheduled job and references its logs; afte... |
math-29 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
ticket.txt requests specific numerical details regarding a customer promotion, and campaign_spec.md... |
science-25 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
A colleague has submitted ticket.txt as a request, and the limits table, the flow log, and the lab ... |
software-34 | software | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Read the README.md file located in this directory, which contains a feature request for the `spend.... |
math-31 | math | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
ticket.txt outlines a check-digit audit task. Create scan_report.csv containing the header scan_id,... |
science-26 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
ticket.txt requests a primer check; the plasmid record and the oligo sheet are located next to it. ... |
science-27 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
ticket.txt requests a primer verification, and the plasmid record and oligo sheet are located adjac... |
science-29 | science | Operate from the current directory by executing shell commands; the environment provides python3 with access to numpy, pandas and Pillow. Once completed, respond with {"answer": "done"} to trigger scoring of your files.
Process the instructions found in request.txt, which is a note from a colleague, using run_export.c... |
Mixed Skills v7: eight-domain verified workspace tasks
One OpenEnv server, 238 deterministic procedurally generated tasks across the eight evaluation domains: software engineering, industrial and physical systems, natural science, office work, finance and economics, math and formal reasoning, cybersecurity, and media production. Each task gives the agent a scratch workspace with input files and a written specification. The agent works with shell commands and is scored by a hidden verifier on the files it leaves behind.
tasks.jsonl lists every task id with its domain and the exact first-turn prompt. The image is
docker.io/chrismun/mixed-env:v7 (linux/amd64); it contains 238 task ids and the submission names the 46 used for training.
Interaction
Each turn the model replies with exactly one JSON object:
{"command": "<shell command>"}runs in the workspace (python3 with numpy, pandas and Pillow). At most 12 commands per episode; each command's output is truncated to its last 1500 characters, so strong solutions inspect withheadand do the work in a script.{"answer": "done"}ends the episode and scores the workspace.
Observations carry the command output, the commands left and. There is no reminder text. Replies that are not a single JSON object end the episode, which is then scored on the workspace as it stands.
Reward
Terminal and in [0, 1]. Every verifier is a weighted set of independent sub-checks recomputed from the task inputs, so partial progress earns partial reward and only a fully correct deliverable scores 1.0. References live only inside the image, agent commands run as an unprivileged user with memory and file-size limits, and verifiers that execute agent code do so in a subprocess with a timeout. An untouched workspace scores at most 0.25 on every task.
Calibration
Tasks were measured with Qwen3.8-27B (thinking off) inside a tool-calling GRPO training harness, because pass rates there differ a lot from a strict JSON-reply driver (the two correlate only 0.25 per task). Each task was sampled 8 to 56 times across profiling and training passes. The 46 training tasks are those whose pooled pass rate falls between about 0.1 and 0.5.
- Pooled mean pass@1 of the 46 tasks: about 0.32, hardest near 0.1 and easiest near 0.5. Selecting on low observed rates regresses upward, so the true start is probably a little higher. A 27B training run on this blend started at a held-out validation score of 0.25 on 11 tasks and a train reward of 0.35.
- About half the tasks are realistic workplace-style jobs: messy CSV, JSON and log inputs, a ticket or README that states the requirements in prose, and distractor files. The rest are cleaner synthetic specifications.
- Every task runs bare: no reply-format reminder and no per-step hint.
- Prompt text: the task statements and the three global strings were rewritten by Qwen3.8-27B under strict gates (every number, file name, identifier, quoted string and JSON example must survive verbatim). The tickets, READMEs and other workspace files written by the task generators were not rewritten.
- No transcript in the profiling runs touched verifier or task source.
Domains
| Domain | Skills exercised |
|---|---|
| software | multi-file bug fixing against hidden tests, implementing modules from a spec, CLI conversion, migration scripts, simulator debugging, performance and dependency problems |
| industrial | sensor log analysis and fault reports, control tuning by simulation, pipe and pump sizing, tariff billing, inventory policy, flow-line simulation |
| science | curve and rate fitting, sequence analysis and protein mass, ODE integration, hypothesis tests, titration equilibria, spectral analysis |
| office | payables reconciliation, meeting-minutes extraction, room scheduling, expense audits, payroll, contact deduplication |
| finance | amortization, market-data analytics, ledger audit, bond pricing, tax lots, FX arbitrage |
| math | exact number theory, proofs by computation, assignment optimization, shortest routes, constructive codes, absorbing Markov chains, impartial games |
| security | log incident analysis, hardening vulnerable code, layered-encoding and crypto forensics, detection rules, advisory matching (all synthetic, defensive) |
| media | subtitle retiming, image pipelines, audio synthesis, SVG charts, timecode conformance, markdown to RSS |
Files
tasks.jsonl:task_id,domain,promptfor each of the 46 training tasks, in training order (domains interleaved).
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