This project aims to foster an open, safe, and collaborative community around the responsible development and use of automations and bots.
We are committed to providing a harassment-free environment for everyone, regardless of age, appearance, disability, ethnicity, gender identity or expression, level of experience, education, socioeconomic status, nationality, political affiliation, religion, sexual orientation, or other personal characteristics.
- Show empathy, respect, and kindness in interactions.
- Accept constructive criticism with openness.
- Take responsibility for mistakes, offer apologies, and learn from the experience.
- Share knowledge and document technical decisions.
- Prioritize security, privacy, and responsible software use.
- Insults, sexualized language or images, harassment, threats, or personal attacks.
- Trolling, deliberate provocations, or continuous disparagement.
- Disclosure of third-party personal information without consent (doxing).
- Any form of social engineering, identity theft, or unauthorized access attempts.
- Encouraging, facilitating, or executing service abuses (spam, scraping that violates TOS, bypassing rate-limits, attacks, fraud, or misuse of APIs).
- Submitting contributions with malicious code, backdoors, or tampered dependencies.
This Code of Conduct applies in all project spaces:
- Repositories, issues, discussions, pull requests, wikis, releases.
- Chat channels, meetings, and related community spaces.
- Public interactions referencing the project or its members.
This project involves automation and possible interactions with third-party services. To protect the community and service providers:
- Respect the Terms of Service and usage limits of the platforms the bot interacts with.
- Prohibited: automating harassment, spam, aggressive scraping, metric manipulation, or any activity that harms services or people.
- Responsible disclosure of vulnerabilities: if you find a security flaw, do not open a public issue. Use the private channel described in “How to Report”.
- Do not publish tokens, credentials, or personal data. Use
.env, GitHub Secrets, and good secret management practices.
- Treat all personal data in accordance with applicable regulations (e.g., GDPR in the EU).
- Minimize data collection. Limit logs and scrub sensitive data.
- Do not share datasets with identifiable information without legal basis and proper anonymization.
- Clearly label bot-generated content and actions when appropriate.
- Avoid harmful biases and review outputs to prevent harm.
- Do not design or contribute to features intended to bypass platform security, moderation, or integrity controls.
The maintenance team may take proportional action against behaviors that violate this Code, including:
- Private observation: Informal request to modify behavior.
- Warning: Formal notification and internal record.
- Temporary limitation: Temporary restriction of participation (issues/PRs/discussions).
- Blocking: Expulsion from project spaces.
- Escalation: If appropriate, report to the platform (GitHub) or relevant entities in case of legal or security risks.
Decisions will consider context, intent, impact, and collaboration history.
If you experience or witness unacceptable behavior:
- Confidential contact:
YOUR_EMAIL@example.com(replace with a contact email)
Alternatives:- GitHub Security Advisory (recommended for security issues): create a Private Vulnerability Report in the repo if enabled.
- Private form: (optional; add link if enabled).
Include, when possible:
- Description of the incident (with dates and URLs of issues/PRs/commits).
- Evidence (screenshots, links).
- Involved users and witnesses.
- Level of urgency (especially in security cases).
Response Commitment: We will make an initial assessment and respond via the same channel within a reasonable time. Your report will be treated confidentially. We will not share your identity without your consent, except as required by law.
- Be impartial: evaluate facts and evidence.
- Request clarifications privately when safe to do so.
- Document warnings and decisions (internal record).
- Apply proportional, temporary measures if possible, and explain the reason.
- In complex cases, seek a second opinion from another maintainer.
Persons subject to measures may request review after a reasonable period, demonstrating understanding of the impact and commitment to change. Send the request to the indicated contact channel.
This Code is inspired by best practices from various open source communities and documents such as the Contributor Covenant (v2.x), adapted to the specific context of automation/bots.
You may reuse and adapt this document in your projects, ideally keeping a note of attribution.
The Spanish version is the reference. If you publish translations, link them here.
Last updated: August 26, 2025 (Europe/Madrid).