HyperFrames Video Entry Point
heygen-com/hyperframes
Entry point for making, editing and rendering videos from HTML compositions with HyperFrames, routing each request to the right workflow.
PR AI review 收敛。用户或 team-lead 要求启动或继续审查—修复循环时使用；供本地实现者或受委派的 review-looper 调用，不用于 GitHub reviewer 产出审查意见或仅处理单条评论。
Install PR AI Review Loop
$ npx skills add ArcReel/ArcReel --skill pr-ai-review-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ArcReel/ArcReel pr-ai-review-loop --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ArcReel/ArcReel.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/pr-ai-review-loop .claude/skills/pr-ai-review-loop && rm -rf skills-srcUse ~/.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/
Install the "pr-ai-review-loop" agent skill from https://github.com/ArcReel/ArcReel/tree/main/.agents/skills/pr-ai-review-loop into .claude/skills/pr-ai-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pr-ai-review-loop", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ArcReel/ArcReel/tree/main/.agents/skills/pr-ai-review-loopType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ArcReel/ArcReel --skill pr-ai-review-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ArcReel/ArcReel pr-ai-review-loop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ArcReel/ArcReel.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/pr-ai-review-loop .agents/skills/pr-ai-review-loop && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "pr-ai-review-loop" agent skill from https://github.com/ArcReel/ArcReel/tree/main/.agents/skills/pr-ai-review-loop into .agents/skills/pr-ai-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pr-ai-review-loop", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ArcReel/ArcReel --skill pr-ai-review-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ArcReel/ArcReel pr-ai-review-loop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ArcReel/ArcReel.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/pr-ai-review-loop .cursor/skills/pr-ai-review-loop && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "pr-ai-review-loop" agent skill from https://github.com/ArcReel/ArcReel/tree/main/.agents/skills/pr-ai-review-loop into .cursor/skills/pr-ai-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pr-ai-review-loop", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ArcReel/ArcReel.git --path .agents/skills/pr-ai-review-loop--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ArcReel/ArcReel --skill pr-ai-review-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ArcReel/ArcReel pr-ai-review-loop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ArcReel/ArcReel.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/pr-ai-review-loop .gemini/skills/pr-ai-review-loop && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "pr-ai-review-loop" agent skill from https://github.com/ArcReel/ArcReel/tree/main/.agents/skills/pr-ai-review-loop into .gemini/skills/pr-ai-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pr-ai-review-loop", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ArcReel/ArcReel pr-ai-review-loopInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ArcReel/ArcReel --skill pr-ai-review-loop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ArcReel/ArcReel.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/pr-ai-review-loop .github/skills/pr-ai-review-loop && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "pr-ai-review-loop" agent skill from https://github.com/ArcReel/ArcReel/tree/main/.agents/skills/pr-ai-review-loop into .github/skills/pr-ai-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pr-ai-review-loop", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ArcReel/ArcReel --skill pr-ai-review-loop -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ArcReel/ArcReel pr-ai-review-loop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ArcReel/ArcReel.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/pr-ai-review-loop .opencode/skills/pr-ai-review-loop && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "pr-ai-review-loop" agent skill from https://github.com/ArcReel/ArcReel/tree/main/.agents/skills/pr-ai-review-loop into .opencode/skills/pr-ai-review-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "pr-ai-review-loop", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
pr-ai-review-loop- GitHub stars
- 5.4k
- Token cost
- ~667 tokens
- SKILL.md length
- 139 words
- Files
- 30 (incl. scripts, references)
- Skills in repo
- 18
- Repo updated
- First seen
- Licence
- AGPL-3.0
At a glance
PR AI review 收敛。用户或 team-lead 要求启动或继续审查—修复循环时使用；供本地实现者或受委派的 review-looper 调用，不用于 GitHub reviewer 产出审查意见或仅处理单条评论。
- Tasks that involve AI video generation
- SKILL.md covers 工程判断, 推进循环, 完成条件 and 预算与交接
- Runs Shell scripts from its folder; calls bash
What it does
PR AI Review Loop is an agent skill from ArcReel/ArcReel. PR AI review 收敛。用户或 team-lead 要求启动或继续审查—修复循环时使用；供本地实现者或受委派的 review-looper 调用，不用于 GitHub reviewer 产出审查意见或仅处理单条评论。
Its SKILL.md is about 670 tokens, which your agent loads only when the skill is triggered. The skill folder holds 33 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/faults.md` and `references/reviewers.md`).
It sits in Media & Creative, covering AI video generation. It works with GitHub. The repository describes itself as: AI Agent 驱动的开源可自部署视频工作台：将小说与剧本转为角色、场景、道具资产、分镜、视频和剪映草稿，支持跨镜头一致性、多供应商与费用追踪 | Self-hosted AI video workspace for stories, storyboards and short-form video production. The licence is AGPL-3.0.
When your agent uses it
- Tasks that involve AI video generation
Example prompts
- “/pr-ai-review-loop”
Requirements
- A Bash shell
What it can do on your machine
Read from SKILL.md and the folder at commit 08ab3b3. 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
Ships 13 files in scripts/ (Shell, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
bash
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
PR AI Review Loop loads about 667 tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 33 tokens; SKILL.md has 139 words of instructions outside code blocks.
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); the scripts in this folder are not scanned.
SKILL.md
The full file from ArcReel/ArcReel at commit 08ab3b3, republished under its AGPL-3.0 licence (© ArcReel). 139 words, ~667 tokens.
Download SKILL.mdSave it as
.claude/skills/pr-ai-review-loop/SKILL.md (or your agent's skills folder). This skill also uses 29 other files; get the full folder from GitHub.- name
- pr-ai-review-loop
- description
- PR AI review 收敛。用户或 team-lead 要求启动或继续审查—修复循环时使用；供本地实现者或受委派的 review-looper 调用，不用于 GitHub reviewer 产出审查意见或仅处理单条评论。
PR AI Review 收敛
以可合并的代码质量为目标。Reviewer 提供待验证的发现，你负责判断问题是否成立、是否应在本 PR 解决，以及怎样修复。完成意味着风险已有处置，而不是所有 bot 都停止提建议。
委派方指发起循环的用户或 team-lead。进入前确认已有非 draft PR，checkout 对应其最新 HEAD，并理解 PR 的验收边界；创建 PR、转为 ready 和合并由委派方或上层流程负责。
工程判断
证据。 从项目契约、真实调用路径和信任边界判断实际后果。可执行的行为缺陷优先用修复前失败、修复后通过的测试验证；难以稳定复现时，用明确的代码因果链或接口契约支撑判断。触发路径存在只是起点，还要说明当前行为为什么错误。安全与数据完整性风险优先核实，修法仍独立判断。
必要性。 优先解决本 PR 引入、加剧或阻碍其验收的缺陷。对存量问题和改进建议，判断是否值得扩大当前变更；不修改或列为非阻塞候选也是有效处置，理由写回 PR。重要风险尚无结论时交委派方裁决。
根因修复。 先理解整批反馈，再按根因选择改动。接受问题不等于接受 reviewer 的 patch；在负责该保证的边界修复，利用已有不变量、抽象和错误处理。以最终设计的清晰度衡量最小修复，而非改动行数。验证后通看整个 PR diff，确认各轮修改仍组成一份连贯的实现。
收敛。 后续审查重点是已接受修复及其回归；新发现仍按上述标准判断。已裁决的议题仅在出现新证据或相关前提变化时重开。多轮围绕同一处加补丁时，回到根因重新整理实现，而不是继续叠加局部防御。
推进循环
首次进入读 reviewers.md，按各家的协议确认审查覆盖、读取发现、补齐必要复审。下列命令从本 skill 目录执行，<repo-root> 始终指向目标 PR checkout；参数和字段定义以脚本 header 为准。
bash scripts/poll.sh --repo-root <repo-root> <PR_NUMBER>
bash scripts/query.sh --repo-root <repo-root> <PR_NUMBER> details <id>...索引用于定位，正文按需读取。no_change 只表示索引未变；上下文丢失时用 query.sh ... index 恢复。合并各家本轮发现、CI 失败和新安全告警，先完成整批判断，再修复、运行受影响质量门并集中 push。对不修改的意见回复依据；同根因的多条意见可以引用同一处置结论。CI 根因已在 main 修复时同步主线并重新验证。
每处置一批记一轮，包括全部以回复结案、没有 push 的批次：
bash scripts/round.sh --repo-root <repo-root> <PR_NUMBER> mark --implemented <n> --pushback <n> --note "根因与处置"--pushback 计入已回复的不修改意见，包括非阻塞处置。CI 修复、rebase 和触发命令本身不计轮。继续拉取状态；仅在缺少审查或检查结果且无可执行动作时，前台运行 bash scripts/wait.sh --repo-root <repo-root> <PR_NUMBER>。超时、配额、权限或 bot 异常按 faults.md 处理。
完成条件
宣布收敛前，确认当前 HEAD 同时满足：
- 覆盖有效：每家参审 reviewer 的审查已完成，覆盖当前变更；允许沿用的情形见 reviewers.md。故障停用单独报告，不能记作通过。
- 发现已处置：本循环所有实质发现，包括历史 inline、review body 和 summary，均已修复、基于证据不修改或明确按非阻塞处置；不存在未裁决的重要风险。处置记录足够，无需等待 bot 同意或撤回。
- 质量门通过：受影响质量门与当前 HEAD 的 required checks 通过，CodeQL 分析和新增安全告警满足 reviewers.md 的安全退出门槛。
checks_failing为空不代表所有检查已完成。
终核重新 poll；对三家各查一次 query.sh ... unacked <bot[bot]>，并用 history / details 补齐尚未核对的正文。旧意见是否遗漏以实际修复和 PR 回复为准，不以 bot 的 ack 数量判断。终核期间 HEAD 改变时，按新 HEAD 重新核对。
预算与交接
默认评估点 3、硬停 6，委派方可覆盖。账本用 round.sh ... show 恢复，接力沿用累计轮数。到评估点简要报告进展：仍在消除真实缺陷，还是主要在往复、扩大范围；判断标准从第一轮起一致。
达到硬停后，只等待最后一批的必要复审并终核；满足完成条件即可退出，否则带着未决事项停止交接。预算耗尽不等于质量通过。
有证据仍无法消解的 reviewer 冲突、重大业务取舍或重要风险，及时交委派方裁决；普通技术分歧自行判断。退出时报告最终 HEAD、轮数、验证结果、关键修复、不修改的依据和未决事项。同一类意见在本 PR 或已知的往期 PR 中第二次出现，而 CODING_STANDARDS.md 与现有检查都没有覆盖时，作为规范候选写进 follow-up，说明它机械可判（适合做成检查）还是需要判断（适合写进 docs/standards/）。超出现有记录或范围的线索作为 follow-up 报告，附依据并区分事实与猜测；已有记录覆盖的不重复提出，分类与价值评估留给委派方。
© ArcReel, AGPL-3.0. 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 29 other files (scripts, references) in .agents/skills/pr-ai-review-loop of ArcReel/ArcReel.
- SKILL.md
- agents/openai.yaml
- references/faults.md
- references/reviewers.md
- scripts/classify_commits.sh
- scripts/poll.sh
- scripts/query.sh
- scripts/repo-context.sh
- scripts/round.sh
- scripts/test_pass_marker.sh
- scripts/test_quota_alerts.sh
- scripts/test_review_body_flags.sh
- scripts/test_round.sh
- scripts/test_wait.sh
- scripts/test_walkthrough_head.sh
- scripts/testdata/coderabbit_inline_review_pr1767.txt
- scripts/testdata/coderabbit_outside_diff_pr1767.txt
- … and 13 more
Open the folder on GitHubat commit 08ab3b3
Compare with similar skills
PR AI Review Loop 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| PR AI Review Loop this skillArcReel/ArcReel | 5.4k | — | ~667 | Automated safety check: Pass | AGPL-3.0 | |
| HyperFrames Video Entry Pointheygen-com/hyperframes | 60k | 3 repos | ~5.2k | Automated safety check: Pass | Apache-2.0 | |
| Issue Assessmentffroliva/gflow-cli | 269 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Video Generationbytedance/deer-flow | 84k | 3 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Video Cover Imageitwanger/toBeBetterJavaer | 18k | — | ~3.3k | Automated safety check: Pass | None | |
| Seedancesongguoxs/seedance-prompt-skill | 2.9k | 1 repos | ~2.5k | Automated safety check: Pass | None |
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Questions about PR AI Review Loop
What does PR AI Review Loop do?
PR AI review 收敛。用户或 team-lead 要求启动或继续审查—修复循环时使用；供本地实现者或受委派的 review-looper 调用，不用于 GitHub reviewer 产出审查意见或仅处理单条评论。. PR AI Review Loop is an agent skill from ArcReel/ArcReel.
When should I use PR AI Review Loop?
PR AI Review Loop fits situations like: tasks that involve AI video generation.
How do I install PR AI Review Loop in Claude Code?
Run `npx skills add ArcReel/ArcReel --skill pr-ai-review-loop -a claude-code`. Or copy the skill folder (.agents/skills/pr-ai-review-loop in ArcReel/ArcReel) into .claude/skills/pr-ai-review-loop in your project. Claude Code loads it when a task matches its description.
How do I install PR AI Review Loop in Codex?
Run `npx skills add ArcReel/ArcReel --skill pr-ai-review-loop -a codex`. Or copy the skill folder (.agents/skills/pr-ai-review-loop in ArcReel/ArcReel) into .agents/skills/pr-ai-review-loop in your project. Codex loads it when a task matches its description.
Can I use PR AI Review Loop 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 ArcReel/ArcReel --skill pr-ai-review-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pr-ai-review-loop, .gemini/skills/pr-ai-review-loop, .github/skills/pr-ai-review-loop and .opencode/skills/pr-ai-review-loop in your project.
What does PR AI Review Loop need to run?
Going by SKILL.md and its folder, PR AI Review Loop needs a shell for the scripts in its folder and the command-line tools its instructions call (bash). Our summary lists: A Bash shell.
Does PR AI Review Loop access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is PR AI Review Loop 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does PR AI Review Loop use?
PR AI Review Loop is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does PR AI Review Loop use?
About 667 tokens (SKILL.md is roughly 2.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.
What are the alternatives to PR AI Review Loop?
Skills that share tags, products or a category with PR AI Review Loop: HyperFrames Video Entry Point (heygen-com/hyperframes, 60k stars), Issue Assessment (ffroliva/gflow-cli, 269 stars), Video Generation (bytedance/deer-flow, 84k stars) and Video Cover Image (itwanger/toBeBetterJavaer, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains PR AI Review Loop?
ArcReel (a GitHub organization) maintains it in ArcReel/ArcReel, which has 5,412 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on October 9, 2026.
Source: ArcReel/ArcReel on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.