ge

name	ge
description	Use when asked to work on a GitHub issue, PR, or discussion. Resolves flexible input (URL, folder, number), confirms with the user, prepares context, and guides the workflow.

ge: Work on a GitHub Issue, PR, or Discussion

Use this skill when asked to work on a GitHub issue, PR, or discussion. It handles the full workflow: resolve what the user means, confirm, prepare or load context, check freshness, handle media, and guide implementation.

Prerequisites

• ge package installed (pip install ge or pip install -e /path/to/ge)
• gh CLI installed and authenticated (gh auth login)
• ffmpeg (optional, for video frame extraction)
• anthropic package + ANTHROPIC_API_KEY (optional, for AI image descriptions)
• ImageMagick (optional, for clipboard montage via copy_images_to_clipboard)

Workflow

Step 0: Resolve what the user means

The user can say "work on THIS" where THIS can be any of:

• A GitHub URL: https://github.com/owner/repo/issues/42
• A folder with pre-prepared context: ~/.cache/ge/owner/repo/issue_42
• A bare number: 42 or #42 (assumes current repo)
• owner/repo#42 or owner/repo/42

Use ge.resolve_target() to parse any of these:

import ge
import subprocess

# Get current repo for bare-number resolution
result = subprocess.run(
    ['gh', 'repo', 'view', '--json', 'nameWithOwner', '-q', '.nameWithOwner'],
    capture_output=True, text=True
)
current_repo = result.stdout.strip()  # e.g. "owner/repo"

# Resolve the user's input
target = ge.resolve_target(USER_INPUT, current_repo=current_repo)

The returned dict contains:

• repo: "owner/repo" (or None)
• number: int
• kind: "issue" | "pr" | "discussion" | None
• context_dir: path to pre-prepared context folder (or None)
• context_md: path to the context markdown file (or None)
• has_prepared_context: bool
• source: how input was resolved ("url", "folder", "number", "repo_number")

Step 1: Confirm with the user (MANDATORY)

Before doing any work, confirm what you resolved. This is not optional.

If the repo differs from the current working directory's repo, flag it:

I resolved your request as issue #42 in other/repo. You're currently in owner/repo — this is a different repository. Should I proceed?

If resolved normally, confirm concisely:

I'll work on issue #520 in cosmograph-org/cosmograph. Pre-prepared context found at ~/.cache/ge/.../issue_520/. Shall I proceed?

Or if no pre-prepared context:

I'll work on issue #42 in owner/repo. No pre-prepared context found — I'll fetch and prepare it now. Shall I proceed?

Wait for the user to confirm before continuing.

Step 2: Load or prepare context

If target['has_prepared_context'] is True:

Read the existing context markdown file directly:

# target['context_md'] is the path to the markdown file
# Read it with the Read tool

Check how fresh it is — the file's prepared_at timestamp is in the JSON. If it's more than a day old, mention it: "Context was prepared on DATE. Want me to refresh it?"

If target['has_prepared_context'] is False:

Prepare fresh context:

ctx = ge.prepare(target['repo'], target['number'])
# ctx['output_dir'] has the path to the context files

This auto-detects type (issue/PR/discussion), fetches everything, downloads media, runs analysis, and generates image descriptions if anthropic is available.

Step 3: Check the recommendation

The context includes an analysis with a recommendation field:

For issues:

• proceed — Active and unresolved. Go ahead.
• investigate — May be partially resolved. Check with the user before working.
• likely_resolved — Closed or strong resolution signals. Confirm with the user.

For PRs:

• proceed — Open and ready for work/review.
• needs_changes — Reviewers requested changes. Address their feedback.
• resolve_conflicts — Merge conflicts exist. Resolve first.
• draft_wip — PR is a draft. May be incomplete.
• already_merged / closed_unmerged — Confirm with user.

IMPORTANT: If recommendation is NOT proceed, explain what you found and ask the user before doing work.

Step 4: Handle media / images

The context document includes downloaded images and — when anthropic is installed and ANTHROPIC_API_KEY is set — AI-generated image descriptions under the "Image Descriptions (AI-generated)" section.

If image descriptions are present (check the "Image Descriptions" section in the markdown):

• Read and incorporate the descriptions into your understanding.
• No manual image pasting needed.

If image descriptions are NOT present but images were downloaded:

1. Describe images programmatically (preferred — if anthropic is available):

   from ge.media import describe_images
   import glob
   imgs = sorted(glob.glob(target['context_dir'] + '/media/*.png'))
   imgs += sorted(glob.glob(target['context_dir'] + '/media/*/*.jpg'))
   if imgs:
       description = describe_images(*imgs)
       print(description)
   

   Tell the user if this fails — they need to know you couldn't analyze the visual content.

2. Create a montage and ask the user to paste (if ImageMagick is available):

   from ge.media import copy_images_to_clipboard
   path = copy_images_to_clipboard(*imgs)
   

   Then tell the user: "A montage of N images has been copied to your clipboard. Please paste it here with Cmd+V so I can see the visual context."

3. Ask the user to paste individual images (last resort): List the specific files and explain why they matter.

Always tell the user if you had problems accessing or analyzing media files.

Step 5: Check referenced code

If the issue mentions specific files, verify they still exist and check recent changes:

git log --oneline -5 -- <referenced_file>

Then read the relevant sections of those files.

Step 6: Work on the issue

Now you have full context. Create a branch, make changes, and submit a PR. Reference the issue number in your commits.

Quick analysis shortcut

If you just need to check whether an issue is worth working on (without preparing full context):

import ge
analysis = ge.analyze_issue('owner/repo', 42)
# or for a PR:
analysis = ge.analyze_pr('owner/repo', 7)

For more details on interpreting analysis results, see the ge-analyze skill.

Python API Reference

Function	Description
ge.resolve_target(input, current_repo=...)	Resolve flexible input to a target dict
ge.prepare(url_or_spec, number)	Full context preparation (auto-detects type)
ge.prepare_issue(repo, number)	Prepare issue context
ge.prepare_pr(repo, number)	Prepare PR context
ge.prepare_discussion(repo, number)	Prepare discussion context
ge.analyze_issue(repo, number)	Staleness analysis (JSON, no media)
ge.analyze_pr(repo, number)	PR review analysis (JSON, no media)
ge.describe_images(*paths)	Describe images via Claude API (vision)
ge.copy_images_to_clipboard(*paths)	Create montage + copy to clipboard
ge.process_all_media(markdown, output_dir)	Download images + extract video frames

Key Principles

1. Always confirm with the user before working. Show what you resolved and wait for approval.
2. Use pre-prepared context when available. Don't re-fetch if has_prepared_context is True (unless stale).
3. Check freshness before coding. Issues may be stale, already fixed, or deprioritized.
4. Use image descriptions when available. Read the "Image Descriptions" section. If missing, generate them with describe_images(). Tell the user if you can't analyze images.
5. Ask the user about ambiguity. If the analysis shows conflicting signals, discuss with the user.
6. Use gh for all GitHub access. This ensures private repo access works via the user's existing auth.