Retentioneering Contributing

What it does

When your agent uses it

• The user says they found a bug
• Wants a feature
• Wrote a workaround worth upstreaming
• Asks how to contribute

Example prompts

• “/retentioneering-contributing”

Requirements

• Python 3
• Node.js
• Compatibility (from SKILL.md): Requires a git checkout of retentioneering-tools, Python >= 3.10 with uv, and Node.js only when JS/widget code is touched. The gh CLI is optional but recommended for PR submission.

Workflow steps

7 steps, taken from the step headings in SKILL.md.

1. 1Capture the observation properly (do this even for "small" ideas)
2. 2Validate against the CURRENT version
3. 3Minimal reproduction (the heart of a bug report)
4. 4Choose the contribution shape
5. 5Implement (when making a PR, not just an issue)
6. 6Pre-flight and submit
7. 7Follow through

What it can do on your machine

Read from SKILL.md and the folder at commit fda32f2. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • uv
  • git
  • gh
  • make
  • npm

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use uv, git, gh and npm, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Requires a git checkout of retentioneering-tools, Python >= 3.10 with uv, and Node.js only when JS/widget code is touched. The gh CLI is optional but recommended for PR submission.

  From compatibility in the SKILL.md frontmatter.

Context cost

Retentioneering Contributing loads about 1.8k tokens when it runs, and up to ~4k if it reads all its reference files. Until then it costs about 132 tokens; SKILL.md has 742 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~132

When it runs · the whole SKILL.md, loaded when a task matches

~1.8k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from retentioneering/retentioneering-tools at commit fda32f2, republished under its Apache-2.0 licence (© retentioneering). 742 words, ~1,841 tokens.

name

retentioneering-contributing

description

Help the user turn their Retentioneering ideas, friction reports, bug findings, or feature needs into high-quality upstream contributions: from capturing and validating the idea, through minimal reproductions and issue drafts, to preparing, testing, and submitting a pull request that follows this repository's conventions. Use when the user says they found a bug, wants a feature, wrote a workaround worth upstreaming, or asks how to contribute, open an issue, or make a PR to retentioneering-tools.

compatibility

Requires a git checkout of retentioneering-tools, Python >= 3.10 with uv, and Node.js only when JS/widget code is touched. The gh CLI is optional but recommended for PR submission.

license

Apache-2.0

metadata.author

retentioneering

metadata.version

1.0.0

metadata.package

retentioneering

metadata.category

developer-tools

metadata.keywords

open source contribution, pull request, bug report, issue template, minimal reproduction, code review, oss workflow, github, retentioneering

metadata.homepage

https://retentioneering.com

metadata.documentation

https://retentioneering.com/docs

metadata.repository

https://github.com/retentioneering/retentioneering-tools

import pandas as pd
from retentioneering import Eventstream
df = pd.DataFrame({"user_id": ["u1","u1","u2"], "event": ["a","b","a"],
                   "timestamp": pd.date_range("2026-01-01", periods=3, freq="1min")})
# EXPECTED: ...       ACTUAL: ...

uv run pre-commit run --all-files      # ruff lint+format, gitleaks, hygiene
uv run pytest tests/ -v                # full suite (CI runs 3.10–3.13)
uv run python docs/scripts/render_pages.py   # if docstrings changed

git push -u origin <branch>
gh pr create --title "<imperative summary>" --body-file pr_body.md

© retentioneering, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in .agents/skills/retentioneering-contributing of retentioneering/retentioneering-tools.

• SKILL.md
• references/proposal-templates.md
• references/repo-conventions.md

Open the folder on GitHubat commit fda32f2