Skip to main content

Review user prompts for evidence-backed improvement in AI coding collaboration.

Project description

Prompt Diary

CI Publish PyPI Coverage budget

Prompt Diary prepares bounded workspaces from local assistant session history and generates evidenced prompt diary reports that help users review and improve how they collaborate with AI coding agents.

The tool targets Python 3.10 and newer. The package exposes report and prompt-diary console commands after installation.

Usage

Install Prompt Diary from PyPI as an isolated uv tool:

uv tool install prompt-diary

Then run:

report --help
prompt-diary --help
report prepare --date 2026-05-12 --timezone Asia/Shanghai

Generation runs an external report-writing model command inside the prepared workspace. The command must read the generated prompt from standard input and create report.md in its current working directory. Configure it before running generate; for example, with Codex CLI:

export PROMPT_DIARY_REPORT_WRITER_COMMAND="codex exec -"
report generate --date 2026-05-12 --timezone Asia/Shanghai

Set PROMPT_DIARY_REPORT_WRITER_TIMEOUT_SECONDS to override the default 600-second writer timeout.

Development

This project uses uv for Python version, environment, dependency, build, and release workflows.

Read docs/src/product.md before designing new features, changing report content, or modifying the generation pipeline. It defines the tool's purposes and principles that downstream design must satisfy.

For environment setup, build commands, type checking, testing, coverage, linting, and pre-submit checks, see the Development Guide. For codebase architecture and API design, see Architecture.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

prompt_diary-0.1.0a2.tar.gz (31.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

prompt_diary-0.1.0a2-py3-none-any.whl (36.6 kB view details)

Uploaded Python 3

File details

Details for the file prompt_diary-0.1.0a2.tar.gz.

File metadata

  • Download URL: prompt_diary-0.1.0a2.tar.gz
  • Upload date:
  • Size: 31.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for prompt_diary-0.1.0a2.tar.gz
Algorithm Hash digest
SHA256 4dd92276676742b1c976d2e6edc67fbbbb4d4aff900e6240e4c8dbb3a9dd063e
MD5 d5c9ae8d40c39ab31eaa16f931048c40
BLAKE2b-256 9815676f1f463f8f8f95d028a43c991891b8a775094f85592b2cd9f2044e8ca2

See more details on using hashes here.

Provenance

The following attestation bundles were made for prompt_diary-0.1.0a2.tar.gz:

Publisher: publish.yml on OptimalCNC/prompt-diary

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file prompt_diary-0.1.0a2-py3-none-any.whl.

File metadata

  • Download URL: prompt_diary-0.1.0a2-py3-none-any.whl
  • Upload date:
  • Size: 36.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for prompt_diary-0.1.0a2-py3-none-any.whl
Algorithm Hash digest
SHA256 ea0724c8a3b3d1fae413c4cc6762b1568a83ad600753142bf2271e02a3bf2d59
MD5 46e5a251ff5c40c3043c8ac2eeca9cd6
BLAKE2b-256 47df353ac924f110617b12165fdbba6a345c2b69c0e83672a2a037727f6a052e

See more details on using hashes here.

Provenance

The following attestation bundles were made for prompt_diary-0.1.0a2-py3-none-any.whl:

Publisher: publish.yml on OptimalCNC/prompt-diary

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page