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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...
industrial-23
industrial
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 analysis is documented in ticket.txt, and the CMMS data export is contained in maintenance.xlsx...
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-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-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-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-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-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...
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-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-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-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-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...
security-32
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. The request is contained in ticket.txt, while the inputs are policy.pdf and review_export.xlsx (usi...
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...
finance-32
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 README.txt located in the current directory contains a request from treasury. Read this fi...
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...
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...
security-33
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. ticket.txt contains the request; the inputs are policy.pdf and review_export.xlsx (use openpyxl: in...
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...
finance-33
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. Treasury has issued a request located in README.txt within the current directory; after reviewing i...
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 ...
media-31
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 request is found in ticket.txt. Use run_of_show.pdf (parsed via pypdf) and clips.csv as inputs....
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...
security-35
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. ticket.txt contains the request; scan_report.pdf and assets.xlsx (using openpyxl: inspect every she...
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....
finance-37
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. Check the README.txt file located in the current directory, which contains a request from group acc...
math-34
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 a verification of claims.xlsx (use openpyxl to open it; formula cells contain c...
office-29
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 POLICY.txt located in the current directory contains instructions from Operations. Review ...
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. ...
software-36
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. ticket.txt contains the request. rates.xlsx serves as the carrier workbook (load it using openpyxl;...
math-35
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 an audit of claims.xlsx (use openpyxl to open it; formula cells contain cached ...
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...
software-37
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 request is contained in ticket.txt. The carrier workbook is rates.xlsx (load it using openpyxl;...
math-36
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 model is described in ticket.txt, its transition table is found in transitions.pdf (extract tex...
science-31
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 submitted ticket.txt; adjacent files include certificate.pdf, a text PDF to be parsed v...
software-38
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 request is in ticket.txt. Adjacent to it are the agreed output schema_sample.json and dictionar...
software-39
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. ticket.txt contains the request, while dictionary_sample.xlsx (openpyxl: merged title row, hidden r...

Mixed Skills v8: eight-domain verified workspace tasks

One OpenEnv server, 278 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:v8 (linux/amd64); it contains 278 task ids and the submission names the 48 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, Pillow and, for file-format tasks, openpyxl, XlsxWriter and pypdf). At most 12 commands per episode; each command's output is truncated to its last 1500 characters, so strong solutions inspect with head and 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 48 training tasks are those whose pooled pass rate falls between about 0.1 and 0.6.

  • Pooled mean pass@1 of the 48 tasks: about 0.34. Selecting on low observed rates regresses upward, so the true start is probably a little higher.
  • 17 of the tasks work on real file formats: multi-sheet .xlsx workbooks (merged headers, hidden rows and sheets, notes sheets) and text PDFs, with a written ticket and one exact output file (a new .xlsx, CSV, JSON or a Python module). The image includes openpyxl, XlsxWriter and pypdf for these. The rest are workplace-style tasks on CSV, JSON and log inputs, plus some 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, and for the file-format tasks most of the requirements live in those files, so the Qwen-written share of the task text is small there.
  • 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, prompt for each of the 48 training tasks, in training order (domains interleaved).
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