Upload local screenshots, images, PDFs, archives, and videos to GitHub, then embed them in pull requests, issues, or comments. Use gh-attach to obtain attachment URLs and download existing GitHub attachments to a specified local destination.
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Uploads a local file (screenshot, image, PDF, zip, video) to GitHub user-attachments, downloads GitHub user-attachments, and embeds local files in a PR, issue, or comment. Use when asked to "attach a screenshot to the PR", "add an image to the issue", "embed before/after screenshots", "attach this file", or "download this GitHub attachment". Powered by `gh-attach`.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
gh attach uploads a file to GitHub's internal user-attachments endpoint (no public API exists) and prints the URL, which GitHub auto-renders (image/video/file) wherever it's pasted. The URL inherits the repo's visibility, so private-repo uploads stay private.
gh extension list | grep -q 'gh attach' || gh extension install sudosubin/gh-attach
Uploads use a GitHub browser session cookie, not the gh token. By default, gh must be authenticated so gh-attach can select the matching browser account. If the wrong account is selected, add --browser <name> --profile <name>. For headless use, set GH_ATTACH_SESSION_TOKEN to the bare user_session cookie value. Treat it as a full account credential.
1. Upload: Use an absolute quoted path. -R is optional inside a repository. For GHES, use -R host/owner/repo. The command prints the URL on one line. GitHub auto-renders it (image/video/file), so use it as-is:
URL=$(gh attach "$FILE" -R <owner>/<repo>)
2. Embed (always --body-file -, e.g. gh pr comment/edit, gh issue comment/edit):
printf '## Screenshots\n\n%s\n' "$URL" | gh pr comment <pr> -R <owner>/<repo> --body-file -
3. Download: Specify the destination explicitly. Private attachments use the active gh token, with browser cookies as an authorization fallback:
gh attach download "$URL" -O "$FILE"
<img width="800" src="$URL"> instead of the bare URL.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.
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Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.
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Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
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Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.
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Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.
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Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.
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