Code of Conduct¶
1. Our Pledge¶
We want this repository to be a place where people can discuss skill design, evaluation, and examples rigorously without turning technical disagreement into personal conflict.
In all project spaces, we commit to: - communicate respectfully and directly - challenge ideas with evidence, not insults - keep safety, privacy, and responsible disclosure in mind - make room for newcomers, experts, and different working styles
2. Expected Behavior¶
- Give concrete, evidence-based feedback in Issues, PRs, Reviews, and Discussions.
- Critique methodology, skills, reports, and examples without attacking the contributor.
- When disagreeing, explain the reasoning, assumptions, and trade-offs.
- Flag unsafe content, secret exposure, or harmful guidance responsibly.
- Keep bilingual governance/docs aligned when you touch them.
- Prefer high-signal contributions over noise, flamebait, or content dumping.
3. Unacceptable Behavior¶
- Harassment, insults, threats, discrimination, or personal attacks.
- Repeated bad-faith accusations (for example, alleging fraud or dishonesty without evidence).
- Deliberate disruption, trolling, brigading, or low-signal spam.
- Posting secrets, private data, exploit payloads, or unsafe instructions irresponsibly.
- Using AI-generated bulk content to flood discussions without review or accountability.
- Any conduct that violates GitHub policies or applicable law.
4. Scope¶
This Code of Conduct applies to: - repository Issues, PRs, Reviews, Discussions, comments, and linked examples - public project-related conversations where someone is clearly acting as a project participant - governance, methodology, evaluation, and output-example discussions related to this repository
5. Reporting¶
If you experience or witness unacceptable behavior:
- For non-sensitive conduct issues, open an Issue with prefix
[CoC]and include a factual timeline. - For sensitive cases, request non-public follow-up and avoid posting private details publicly.
- If the issue also involves secrets, exploit details, or unsafe content, follow SECURITY.md instead of posting full details publicly.
Useful report details: - where it happened - links or screenshots if available - factual context - what outcome you want
6. Enforcement Principles¶
Maintainers will review reports based on available evidence and aim to provide an initial response within 3 business days.
Enforcement principles: - fairness: decisions should be evidence-based - privacy: share only what is necessary - proportionality: mild issues may start with warning/correction; severe or repeated issues may escalate - project fit: this repository allows strong technical disagreement, but not abusive behavior
7. Possible Consequences¶
Depending on severity, maintainers may: - issue a warning - ask for edits or removal of inappropriate content - lock or limit participation in a thread - temporarily suspend participation - permanently ban participation
8. Relationship to Security¶
This repository contains skills, examples, and helper scripts that may influence real-world AI behavior.
If a conduct issue also creates a safety or disclosure risk, maintainers may handle it under both this policy and SECURITY.md.
9. Attribution¶
This policy is informed by Contributor Covenant practices and adapted for a repository centered on skill methodology, examples, evaluation reports, and output artifacts.