Scrapegraph-ai AGENTS.md

Repository instructions for ScrapeGraphAI, including its required branch, release, testing, and pull-request workflow.

In plain words
What is it for?
Use them when developing, testing, committing, pushing, or opening a pull request for the project.
Why use it?
They prevent changes from being made on the wrong branch and document the commands and checks expected before submitting work.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/scrapegraphai/scrapegraph-ai/agents-md
Clone the repo
git clone --depth 1 https://github.com/ScrapeGraphAI/Scrapegraph-ai

Made for: Codex, OpenCode.

Per session 1,314 This file is loaded in full into every session.
When invoked 1,314 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.01314 $0.01314
Opus 5 $0.00657 $0.00657
Sonnet 5 $0.00263 $0.00263
Haiku 4.5 $0.00131 $0.00131

Measured 2d ago against content hash dbbe4eda0e80, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Scrapegraph-ai AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Instructions for AI coding agents (Claude Code, Codex, Cursor, Copilot agents, …) working on ScrapeGraphAI. Human contributors should read CONTRIBUTING.md; everything here is in addition to it.


1. Golden rule: everything goes to pre/beta

main is never written to directly. All work is based on and merged into pre/beta.

pre/beta is the prerelease branch: pushes to it publish a beta prerelease via semantic-release (see .releaserc.yml). main only receives releases when a maintainer promotes pre/beta.

# 1. always start from an up-to-date pre/beta
git fetch origin
git checkout -b feat/my-change origin/pre/beta

# 2. commit your work
git add <only the files you touched>
git commit -m "feat(nodes): add X"

# 3. push and open the PR against pre/beta
git push -u origin feat/my-change
gh pr create --base pre/beta --title "feat(nodes): add X" --body "..."

Checklist before you commit:

  • The branch is based on origin/pre/beta (git merge-base --is-ancestor origin/pre/beta HEAD).
  • The PR base is pre/beta, not main.
  • No commits directly on main or pre/beta, no force-push to either.
  • One logical change per branch/PR.

If a task genuinely requires targeting main (e.g. a hotfix on a released version), stop and ask a maintainer first.

2. Environment setup

Python >=3.12, dependencies managed with uv:

uv sync                     # create the venv and install deps
uv run pre-commit install   # install the git hooks

Never hand-edit uv.lock; regenerate it with uv lock / uv sync and commit the result only when you actually changed dependencies in pyproject.toml.

3. Checks to run before pushing

make lint         # ruff + black --check + isort --check-only
make type-check   # mypy (strict)
make test         # pytest with coverage
make pre-commit   # run all hooks on all files

Run at least make lint and the tests covering what you touched. Report the real result: if something fails or you skipped a step, say so in the PR description instead of implying a clean run.

Read the full file on GitHub · 137 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 137 lines · 1,314 tokens per session scan A dbbe4eda0e80

Subscribe to this mod's changes

Scrapegraph-ai AGENTS.md is an instructions file published in the GitHub repository ScrapeGraphAI/Scrapegraph-ai (30,345 stars, last pushed 5d ago), licensed MIT. It adds 1,314 tokens to every session, about $0.0066 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.