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무료GitHub에 공개

gh-issues

Use when creating, searching, updating, or managing GitHub issues via CLI. Triggers: "issue", "create issue", "gh issue", "task tracking", "context", "handoff", "resume task", "session context", "save progress", "active tasks", "in-progress", "my tasks", "open issues". Covers: gh commands, bulk operations, JSON/jq, search filters, issue-to-PR workflow, AI session context storage, task workflow with labels.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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포함된 파일(5)

  • SKILL.md7.1 KB
  • assets/illustration.png488.2 KB
  • README.md1.7 KB
  • README.ru.md2.5 KB
  • references/context-template.md2.1 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

GitHub Issues CLI

Efficient GitHub Issues management via gh CLI with AI session context storage.

Table of Contents

  1. Quick Reference
  2. JSON Output
  3. Search Filters
  4. Bulk Operations
  5. Issue to PR Workflow
  6. Milestones
  7. AI Session Context
  8. Task Workflow
  9. Examples
  10. Common Mistakes

Quick Reference

TaskCommand
Create issuegh issue create -t "Title" -b "Body" -l bug -a @me
Active tasksgh issue list -l in-progress -s open
List open bugsgh issue list -l bug -s open
View as JSONgh issue view 123 --json number,title,body,labels,state
Close with commentgh issue close 123 -c "Fixed in #456"
Edit labelsgh issue edit 123 --add-label priority:high
Start workgh issue edit 45 --add-label in-progress
Create branchgh issue develop 123 --checkout
Load contextgh issue view 45 --json comments --jq '.comments[] | select(.body | contains("AI-CONTEXT"))'

JSON Output Patterns

Always use --json for parsing. Fields: number, title, body, state, labels, assignees, milestone, author, createdAt, updatedAt, comments, url.

gh issue view 123 --json number,title,labels,state
gh issue list --json number,title,labels --jq '.[] | select(.labels[].name == "bug")'
gh issue list -l bug --json number --jq '.[].number'

Advanced Search Filters

gh issue list --search "is:open author:username"
gh issue list --search "created:>=2026-01-01 created:<=2026-01-07"
gh issue list --search "label:bug label:priority:high"
gh issue list --search "is:open -label:wontfix"
gh issue list --search "milestone:v2.0"

Bulk Operations

gh issue edit 10 15 20 --add-label "priority:high"
gh issue close 10 15 20 -c "Duplicate of #5"
gh issue list -l needs-triage --json number --jq '.[].number' | \
  xargs -I{} gh issue edit {} --add-label reviewed

Issue to PR Workflow

gh issue develop 123 --checkout          # Create branch from issue
git add . && git commit -m "fix: #123"   # Commit with reference
gh pr create --fill                       # Create PR (auto-links)
gh issue close 123 -c "Fixed in PR #456" # Close when merged

Milestones via API

gh api repos/:owner/:repo/milestones --jq '.[].title'
gh issue edit 123 -m "v2.0"

AI Session Context

Store session context in GitHub issues for seamless task handoff.

Read Context

# Get AI context from issue comments
gh issue view 45 --json comments --jq '
  .comments[] | select(.body | contains("AI-CONTEXT:START")) | .body
'

# Get comment ID for updates
gh issue view 45 --json comments --jq '
  .comments[] | select(.body | contains("AI-CONTEXT:START")) | .id
'

Save Context

# Create new context comment
gh issue comment 45 --body-file .ai-context.md

# Update existing (replace COMMENT_ID)
gh api repos/:owner/:repo/issues/comments/COMMENT_ID \
  --method PATCH -f body="$(cat .ai-context.md)"

Context Template

See references/context-template.md for full template. Minimal version:

<!-- AI-CONTEXT:START -->
## Context | IN_PROGRESS
**Files:** `file.py:45`, `other.py:120`
**Done:** task1, task2
**Next:** next task
**Resume:** One-line summary for cold start
<!-- AI-CONTEXT:END -->

Workflow

  1. Start work — load context from issue
  2. Work on task — track progress mentally
  3. Pause/Stop — save context to issue comment
  4. Resume later — load context, continue

Task Workflow

Manage issue lifecycle with labels.

Labels

LabelMeaning
backlogIn queue
in-progressActive work
blockedBlocked
reviewNeeds review

View Active Tasks

# My active issues
gh issue list -l in-progress -s open

# All my assigned issues
gh issue list --assignee @me -s open

# Issues with context
gh issue list -s open --json number,title,labels --jq '
  .[] | select(.labels[].name == "in-progress") | "#\(.number): \(.title)"
'

Start Working

# Mark as in-progress
gh issue edit 45 --add-label in-progress --remove-label backlog

# View issue + load context
gh issue view 45 --json number,title,body,comments --jq '{
  number, title, body,
  context: (.comments[] | select(.body | contains("AI-CONTEXT")) | .body) // "No context"
}'

Pause/Block

# Mark as blocked
gh issue edit 45 --add-label blocked --remove-label in-progress

# Add blocking comment
gh issue comment 45 --body "Blocked: waiting for API access"

Complete

# Close with comment
gh issue close 45 -c "Done in commit abc123"

# Or close via PR (auto-closes if PR body contains "Fixes #45")

Examples

Create Issue for Task

gh issue create -t "Simplify bot flow" -b "## Problem
Bot stopped converting. Current flow is complex.

## Reference
Simple flow example from competitor.

## Tasks
- [ ] Analyze current flow
- [ ] Create new diagram
- [ ] Implement"

Start Working on Issue

# 1. View issue with context
gh issue view 45 --json number,title,body,comments --jq '{
  number, title, body,
  context: (.comments[] | select(.body | contains("AI-CONTEXT")) | .body) // "No context"
}'

# 2. Create branch
gh issue develop 45 --checkout

# 3. Work...

Save Progress Before Stopping

# Create context file
cat > .ai-context.md << 'EOF'
<!-- AI-CONTEXT:START -->
## AI Session Context
_Last updated: 2026-01-07 16:00_

### Status
**IN_PROGRESS**

### Progress
- [x] Analyzed current flow
- [ ] Create new diagram

### Key Files
- `handlers/start.py:45-78` — start handler
- `data/courses.yaml` — config

### Next Steps
1. Draw simplified flow
2. Implement changes

### Resume Context
Simplifying bot flow. Analyzed current state. Next: create diagram.
<!-- AI-CONTEXT:END -->
EOF

# Save to issue
gh issue comment 45 --body-file .ai-context.md

Resume Work

# Load context
CONTEXT=$(gh issue view 45 --json comments --jq '
  .comments[] | select(.body | contains("AI-CONTEXT")) | .body
' 2>/dev/null)

echo "$CONTEXT"
# Continue from where you left off...

Common Mistakes

MistakeFix
Missing --jsonAlways --json field1,field2
Loop instead of multi-arggh issue edit 1 2 3
Using grep on outputUse --jq
Forgot -s all for closedDefault is open only
{owner}/{repo} in APIUse :owner/:repo
Duplicate context commentsUpdate existing, don't create new

리뷰

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같은 저장소의 스킬

Orchestrate iterative visual style searches with branch prompts, decision graphs, feedback loops, and final direction selection.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

serejaris/personal-corp-os2312026년 10월 21일 업데이트

Audits the agent rules in the current folder (AGENTS.md, nested AGENTS.md files) and the skill descriptions the agent sees at start, then reports what to cut, move or rewrite and edits only after the user says yes. Use on «аудит правил», «проверь AGENTS.md», «почему агент не слушается правил», «проверь скиллы».

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

serejaris/personal-corp-os2312026년 10월 21일 업데이트

avatar

무료

Робот агента Personal Corp. Агент делает себе голову робота из набора деталей, хранит её в штабе в stack/avatars.json и кладёт в штаб страницу avatar/robot.html, где робот стоит за партой своего штаба и вокруг видны отделы, без сервера и интернета. На уроке по ссылке входа с экрана урока робот входит в живой класс и горит маячком, пока агент работает. Триггеры /avatar, /avatar <ссылка входа>, сделай себе аватар, покажи своего робота, приди на урок.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

serejaris/personal-corp-os2312026년 10월 21일 업데이트

benchmark

무료

Use when choosing between engines or models for an agent pipeline and the answer must come from measurement on your own data, not from marketing pages: speech recognition for meeting recordings, the model that turns a transcript into notes, the critic model that checks it. Runs every variant in an isolated container, measures time, cost per hour of input (USD and RUB, with price source and date) and quality (WER/CER and course terms for ASR; code checks plus a judge of a different model for LLM steps), writes results.json/csv and one static analytics page. Triggers on "бенчмарк", "сравни движки", "сколько стоит час записи", "какую модель взять для пайплайна", "benchmark the pipeline", "compare ASR engines".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

serejaris/personal-corp-os2312026년 10월 21일 업데이트

Use when user asks for Claude Code usage stats, weekly analytics, project activity summary, or wants to see what projects were worked on. Triggers on "аналитика", "статистика claude", "cc stats", "weekly report", "что делал"

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

serejaris/personal-corp-os2312026년 10월 21일 업데이트

Use when needing strategic project analysis from multiple independent expert perspectives. Triggers on business decisions, growth strategy, product direction, competitive analysis, or any situation where diverse C-level opinions reduce blind spots

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

serejaris/personal-corp-os2312026년 10월 21일 업데이트

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