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Distribution And Discovery Checklist

Use this checklist after major updates or releases. The goal is accurate discovery, not hype.

Indexing Basics

  • Confirm the repository is public.
  • Confirm GitHub Pages is enabled and points to docs/ on main.
  • Confirm the Pages homepage is set as the repository website.
  • Confirm docs/sitemap.xml and docs/robots.txt are reachable.
  • Share the GitHub repository URL and Pages URL from public pages that search engines can crawl.

Search engines may still take days or longer to index a new repository. Backlinks and real activity help discovery.

Hugging Face Mirror

The repository is mirrored to the Hugging Face Hub model repo cy0307/awesome-loop-engineering for discovery within the AI/ML community. The daily maintenance routine syncs it after each GitHub push.

  • The mirror tracks the full GitHub tree (docs, patterns, examples, schema, scripts).
  • The HF copy of README.md carries a model-card YAML header (license, language, tags). This header is HF-only: it must never be added to the GitHub README.md, because the YAML list items break awesome-lint.
  • Sync uses the hf upload CLI against a staging copy with the header prepended, so the GitHub working tree stays header-free. The token lives in the local Hugging Face cache; no token is committed.

Launch Copy

Use posts/launch.md when you want a longer article-style launch post.

Short Post 

Awesome Loop Engineering v0.1.0 is live.

Loop Engineering is the layer above prompt, context, and harness engineering: designing recurring AI-agent systems that discover work, delegate to agents, verify results, persist state, decide next actions, and run again.

Repo:
https://github.com/ChaoYue0307/awesome-loop-engineering

Longer Post 

Awesome Loop Engineering v0.1.0 is live.

The repo curates resources and practical patterns for an emerging AI/coding-agent practice: moving from turn-by-turn prompting to recurring systems that prompt, supervise, verify, persist state, and rerun agents.

It includes:

- curated papers, blogs, docs, tools, benchmarks, and patterns
- manifesto, taxonomy, comparison guide, anti-patterns, and sourced signals
- loop contract schema with validated examples
- pattern library for PR babysitting, CI repair, docs drift, deploy verification, and feedback clustering
- community gallery for real-world loop examples

Contributions and corrections are welcome:
https://github.com/ChaoYue0307/awesome-loop-engineering

Where To Share

  • X/Twitter thread with the cover image and canonical definition.
  • LinkedIn post focused on the prompt/context/harness/loop stack.
  • Hacker News or Reddit only if framed as a useful field guide, not a launch announcement.
  • Relevant GitHub issues or discussions where Loop Engineering, coding agents, or agent workflows are already being discussed.
  • Authors and maintainers cited in the repo, asking for corrections or stronger canonical links.
  • The repository's own Discussions, using DISCUSSIONS.md for starter prompts and scope guidance.

Outreach Targets

Use OUTREACH.md for wording.

  • Direct Loop Engineering article authors.
  • Agent runtime maintainers with scheduling, goals, hooks, worktrees, skills, plugins, or subagents.
  • Benchmark maintainers for long-horizon coding agents.
  • Builders who can contribute real PR babysitting, CI repair, docs drift, deploy verification, or feedback clustering loops.

Awesome List Submission

Use AWESOME_SUBMISSION.md for the upstream checklist, timing rule, suggested entry, and PR body.

Before submitting to any awesome list:

  1. Verify all links pass.
  2. Confirm the README has a narrow scope and contribution guidelines.
  3. Confirm the license is visible and correct.
  4. Confirm the repo has a release and working CI.
  5. Submit only where the maintainers accept related awesome-list entries.

Candidate places:

  • sindresorhus/awesome
  • adjacent prompt, context, harness, and agent engineering lists that accept PRs for related resources

Accuracy Rules

  • Do not claim that Loop Engineering is a finished standard.
  • Do not imply cited authors endorse this repository unless they explicitly do.
  • Prefer "early field guide" or "curated map" over "definitive source".
  • Keep all claims linked to public, inspectable sources.