license: apache-2.0
language:
- en
pretty_name: skycmd secrets jev
task_categories:
- text-classification
tags:
- skycmd
- typed-decisions
- system-one
configs:
- config_name: secret_bench
data_files: data/secret_bench.parquet
- config_name: secret_synth
data_files: data/secret_synth.parquet
skycmd secrets jev
Short texts (.env, code, configs, curl, logs, diffs) with four questions each: is a usable secret exposed, which service issued it, what kind of value it is, on which line. Every key is generated: it follows its provider's public format with a random body, so none is a real key. secret_bench uses four file types the training set never shows.
Part of skycmd, tiny decision models trained from scratch in Rust that run in the
browser. Written by sky-data secret-jev (seed 1234) at commit 6cbcce8c.
Licences of every set: DATA_LICENSES.md.
Each row is one typed decision question (docs/SPEC.md):
| field | type | meaning |
|---|---|---|
src |
string | source |
t |
string | choice, score or noul |
ins |
string | the question |
opts |
list of strings | the options, rendered as text |
state |
string | the state the question is about |
target |
list of floats | a probability per option (soft or one-hot) |
split |
string | train, val or test |
Licence
Apache-2.0: generated by skycmd's own code, no third-party data.
Files
| file | rows |
|---|---|
data/secret_bench.parquet |
7,984 |
data/secret_synth.parquet |
193,258 |
from datasets import load_dataset
ds = load_dataset("maxgfr/skycmd-secrets", "secret_bench")
skycmd wrote no row with a language model: the targets come from the upstream labels (some upstream sets carry their own teacher soft labels, see their cards), the games' oracles or our generators.