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Agent skill

Rpa Init

by coddy-project in coddy-project/coddy-agent

Run when the user invokes /rpa-init or asks to onboard or warm up context on a repository.

MITAuto-check passedProductivity & Automation

Install Rpa Init

skills CLI
$ npx skills add coddy-project/coddy-agent --skill rpa-init -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install coddy-project/coddy-agent rpa-init --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/coddy-project/coddy-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/internal/skills/bundled/rpa-init .claude/skills/rpa-init && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
rpa-init
GitHub stars
167
Token cost
~728 tokens
SKILL.md length
303 words
Files
3
Skills in repo
6
Repo updated
First seen
Licence
MIT

At a glance

Run when the user invokes /rpa-init or asks to onboard or warm up context on a repository.

  • Works in 4 steps: Read application source, docs, and tests… → Dev environment - install dependencies… → Locate how tests are run. Default for… → …
  • Invokes /rpa-init
  • SKILL.md covers Intent, Preconditions you must verify…, Workflow and Report template, plus 1 more section
  • Calls pytest, python and pip

What it does

Rpa Init is an agent skill from coddy-project/coddy-agent. Run when the user invokes /rpa-init or asks to onboard or warm up context on a repository. The agent studies code, reads documentation and test code, sets up the dev environment as the project expects, runs tests, and writes a short project report. No extra user brief is required.

Its SKILL.md is about 730 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `README.md`).

It sits in Productivity & Automation, covering Workflow automation. It works with Python and Git. The repository describes itself as: General-purpose agent in one static Go binary: console TUI, ACP server for editors, OpenAI-compatible API with embedded web UI, Telegram gateway, cron scheduler, swarm relay… The licence is MIT.

When your agent uses it

  • Invokes /rpa-init
  • Asks to onboard
  • Warm up context on a repository

Example prompts

  • “/rpa-init”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Read application source, docs, and tests (test code is part of the specification).
  2. Dev environment - install dependencies and prepare the environment the repo documents (for example python -m venv .venv, pip install -e…
  3. Locate how tests are run. Default for Python: pytest via .venv when present. Respect pytest.ini, pyproject.toml, or tox / nox if present.
  4. Identify entrypoints: README, docs/, package layout, main modules, CLI.

What it can do on your machine

Read from SKILL.md and the folder at commit 4a416a0. 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:

    • pytest
    • python
    • pip
    • uv
    • npm
    • git

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

  • Network

    No URLs in SKILL.md. Its commands use pip, uv, npm and git, 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.

Context cost

Rpa Init loads about 728 tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 303 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~73
When it runs · the whole SKILL.md, loaded when a task matches
~728

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

Auto-check passed

The automated check found no risky patterns in SKILL.md.

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 coddy-project/coddy-agent at commit 4a416a0, republished under its MIT licence (© coddy-project). 303 words, ~728 tokens.

Download SKILL.mdSave it as .claude/skills/rpa-init/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
rpa-init
description
Run when the user invokes /rpa-init or asks to onboard or warm up context on a repository. The agent studies code, reads documentation and test code, sets up the dev environment as the project expects, runs tests, and writes a short project report. No extra user brief is required.
metadata.version
1.0.2

RPA project initialization (context warm-up)

Intent

Treat automated tests as the project long-term memory. Initialization maps documented intent, behavior encoded in tests, and implementation. Prefer learning from tests and docs before inferring only from production code.

Preconditions you must verify yourself

  1. Read application source, docs, and tests (test code is part of the specification).
  2. Dev environment - install dependencies and prepare the environment the repo documents (for example python -m venv .venv, pip install -e ., uv sync, npm ci, or commands from README / CI). If the stack is not Python, follow that ecosystem's norms.
  3. Locate how tests are run. Default for Python: pytest via .venv when present. Respect pytest.ini, pyproject.toml, or tox / nox if present.
  4. Identify entrypoints: README, docs/, package layout, main modules, CLI.

Workflow

  1. Optional git update — if the directory is a git repository and the user has not asked to stay on the current commit, run git pull to refresh the local copy before analysis.

  2. Scan repository structure (layout, monorepo packages if any).

  3. Read user-facing documentation and specs.

  4. Study test code (naming, fixtures, markers, integration vs unit). This is the BDD-facing view of expected behavior.

  5. Set up dev environment so tests can run (create venv, install deps, any documented bootstrap). Note blockers if setup cannot be completed.

  6. Run the test suite, for example:

    bash
    .venv/bin/pytest -q

    If tests fail, record where and why (do not fix unless the user asked).

  7. Summarize in a concise report (see template). Use English for code-related terms if the codebase uses English; respond in the user's language for narrative.

Report template

Use this structure (adapt if needed):

markdown
## Project snapshot
- Purpose (one paragraph)
- Main packages and boundaries

## Dev environment
- What was installed or configured (venv, package manager, key commands)

## How to run tests
- Commands actually used

## Behavior from tests
- Scenarios covered by tests (bullets)
- Gaps (important paths with weak or missing tests)

## Risks and notes
- Flaky tests, secrets, external services

## Suggested next steps
- 1 to 3 follow-ups

Constraints

  • Comments in any new code: English only.
  • Do not add secrets or keys.
  • If the repository is not Python, still follow the same pattern: official install and test commands, then report.

© coddy-project, MIT. 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 in internal/skills/bundled/rpa-init of coddy-project/coddy-agent.

  • SKILL.md
  • LICENSE
  • README.md

Open the folder on GitHubat commit 4a416a0

Compare with similar skills

Rpa Init next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Rpa Init compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Rpa Init this skillcoddy-project/coddy-agent167—~728Automated safety check: PassMIT
Hook Factoryalirezarezvani/claude-code-skill-factory880—~3.1kAutomated safety check: PassMIT
N8n CLIn8n-io/n8n207k—~3kAutomated safety check: PassCustom licence
Skyvern Browser AutomationSkyvern-AI/skyvern23k—~1.9kAutomated safety check: PassAGPL-3.0
Robocorp Automationrobocorp/robocorp653—~3.3kAutomated safety check: PassApache-2.0
Native Python in n8n Code Nodesczlonkowski/n8n-skills6.4k—~2.8kAutomated safety check: PassMIT

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Works with

Categories

Questions about Rpa Init

What does Rpa Init do?

Run when the user invokes /rpa-init or asks to onboard or warm up context on a repository. Rpa Init is an agent skill from coddy-project/coddy-agent. Run when the user invokes /rpa-init or asks to onboard or warm up context on a repository.

When should I use Rpa Init?

Rpa Init fits situations like: invokes /rpa-init; asks to onboard; warm up context on a repository.

How do I install Rpa Init in Claude Code?

Run `npx skills add coddy-project/coddy-agent --skill rpa-init -a claude-code`. Or copy the skill folder (internal/skills/bundled/rpa-init in coddy-project/coddy-agent) into .claude/skills/rpa-init in your project. Claude Code loads it when a task matches its description.

How do I install Rpa Init in Codex?

Run `npx skills add coddy-project/coddy-agent --skill rpa-init -a codex`. Or copy the skill folder (internal/skills/bundled/rpa-init in coddy-project/coddy-agent) into .agents/skills/rpa-init in your project. Codex loads it when a task matches its description.

Can I use Rpa Init in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add coddy-project/coddy-agent --skill rpa-init -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rpa-init, .gemini/skills/rpa-init, .github/skills/rpa-init and .opencode/skills/rpa-init in your project.

What does Rpa Init need to run?

Going by SKILL.md and its folder, Rpa Init needs the command-line tools its instructions call (pytest, python, pip, uv, npm and git). Our summary lists: Python 3.

Does Rpa Init access the network?

SKILL.md contains no URLs. Its commands use pip, uv, npm and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Rpa Init safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Rpa Init use?

Rpa Init is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Rpa Init use?

About 728 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Rpa Init?

Skills that share tags, products or a category with Rpa Init: Hook Factory (alirezarezvani/claude-code-skill-factory, 880 stars), N8n CLI (n8n-io/n8n, 207k stars), Skyvern Browser Automation (Skyvern-AI/skyvern, 23k stars) and Robocorp Automation (robocorp/robocorp, 653 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Rpa Init?

coddy-project (a GitHub organization) maintains it in coddy-project/coddy-agent, which has 167 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on October 9, 2026.

Source: coddy-project/coddy-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.