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agentprov

AgentPROV turns agent executions into a source-preserving, evidence-qualified canonical record, and derives W3C PROV from that record. The executions can be captured live or released by other research projects. Every derived PROV statement names its evidence class, the rule that produced it, and the field of the record that justifies it. Corpora are hash-chained from the original raw bytes to the final graph. You can verify and recompute them without re-running any model.

This package is the agentprov command-line program and library. It installs the capture library (agentprov-capture) with it; the draft-only Zenodo uploader (agentprov-zenodo) comes with the zenodo extra.

Install

Python 3.14.8 or later:

pip install agentprov              # or: uv tool install agentprov
pip install "agentprov[zenodo]"    # with the draft-only Zenodo uploader
agentprov info                     # versions, the source registry, extras, host isolation grade
agentprov --help

The desktop app is a separate download for macOS, Windows and Linux, on the releases page. Live runs need the repository checkout: the benchmark backends are separate projects that this package does not contain.

What it does

  • Import released agent logs (48 sources in 13 formats, single-agent tool-calling traces) and live captures into one canonical execution record (aer/0.2), through isolated, resource-limited workers.
  • Derive semantic annotations (sem/0.1) and W3C PROV-JSON in three bundles: core (observed and derived statements), inference and assessment (agentprov-prov/0.1).
  • Validate each stage, verify a corpus's hash chain against its root digest, and recompute the derivation byte for byte without calling a model.
  • Package a corpus with its datasheet and checksums for an offline deposit; package never uploads. The separate uploader creates unpublished Zenodo drafts only, and publishing is always done by hand on Zenodo.

The user guide walks through each step on a small demo corpus, and its command reference lists every command's --help.

Citation

@software{jones_agentprov_2026,
  author  = {Jones, Nicholas},
  title   = {AgentPROV: execution provenance for LLM-agent security research},
  version = {0.1.1},
  year    = {2026},
  license = {MIT},
  url     = {https://github.com/nickjones39/AgentPROV}
}

Licence

MIT, © 2026 Nicholas Jones. Third-party code and data licences are listed in THIRD_PARTY_NOTICES.md.

Metadata

Release files for agentprov 0.1.1

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Source distribution (sdist)

Source distribution for agentprov 0.1.1
File Size Uploaded Provenance Actions
agentprov-0.1.1.tar.gz 2.8 MB Without provenance Details for agentprov-0.1.1.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for agentprov 0.1.1
File Interpreter ABI Platform Actions
agentprov-0.1.1-py3-none-any.whl Python 3 none any Details for agentprov-0.1.1-py3-none-any.whl

Total release size: 6.1 MB

Release files / agentprov-0.1.1.tar.gz

Download URL agentprov-0.1.1.tar.gz
Size 2.8 MB
Tags Source
SHA-256 checksum
How to use checksums
c24f46ed0d0ff81d76f2e0dd946890a191b005055b1f0072f6e1a9651297f026
BLAKE2b-256 checksum
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d25b34c85412d18d7dda1475e862a1073f7e9e44201484c9d0489a84e83aa92c
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No
Uploaded via twine/7.0.0 CPython/3.14.9

Release files / agentprov-0.1.1-py3-none-any.whl

Download URL agentprov-0.1.1-py3-none-any.whl
Size 3.3 MB
Tags Python 3
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ef7eb573521080a69b496fbb2bb89974e57627812be7f0208be747122d7a7000
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b60a7987cb531127f8ad7d5081c42485f2fae66a486db81f09308778b22f8e47
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No
Uploaded via twine/7.0.0 CPython/3.14.9

Security for agentprov 0.1.1

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