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Create Pr

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yonatangross
create-pr

Creates GitHub pull requests with pre-flight validation, conventional title formatting, and structured summary generation. Runs parallel checks (tests, lint, type-check, security) before opening. Supports feature, bugfix, refactor, and hotfix PR types with milestone assignment via gh CLI. Invoke only if the operator named it; an everyday `gh pr create` stays plain tooling. Use when opening PRs or submitting code for review.

Overview

Publisheryonatangross
Repositoryorchestkit
Skill namecreate-pr
Stars
298
Forks
35
Bundled files
19
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 19 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yonatangross on GitHub. Read the source before you install it.

Installation

Install the Create Pr AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/create-pr
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yonatangross/orchestkit.git /tmp/orchestkit
mkdir -p .claude/skills
cp -r /tmp/orchestkit/plugins/ork/skills/create-pr .claude/skills/create-pr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Pr in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Create Pr on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Create Pr is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Create Pull Request

Comprehensive PR creation with validation. All output goes directly to GitHub PR.

Quick Start

bash
create-pr
create-pr "Add user authentication"

CC ≥ 2.1.119 multi-host note (M122): PR creation works against GitHub, GitLab, Bitbucket, and GitHub Enterprise. Detect the target host from the configured remote (git remote -v) and branch on the host family for the right CLI:

Host familyCLI
github / github-enterprisegh pr create (with GH_HOST=<host> for GHE)
gitlab / gitlab-selfglab mr create
bitbucketbb pr create

Custom enterprise URLs: prUrlTemplate setting (see src/skills/configure/ and src/skills/chain-patterns/references/pr-from-platform.md).

Argument Resolution

python
TITLE = "$ARGUMENTS"  # Optional PR title, e.g., "Add user authentication"
# If provided, use as PR title. If empty, generate from branch/commits.
# $ARGUMENTS[0] is the first token (CC 2.1.59 indexed access)

Base Branch Resolution

Derive the base branch from the remote. Never hardcode dev or main; repos differ.

bash
BASE=$(git symbolic-ref --short refs/remotes/origin/HEAD 2>/dev/null | sed 's|^origin/||')
BASE=${BASE:-main}   # ref missing (fresh/shallow clone)? run: git remote set-head origin -a

Every $BASE below refers to this value.

Stacked on another open PR

When the work depends on an open PR ("a PR that depends on PR #50"), that PR's head branch is the base, not $BASE:

bash
PARENT=50
PARENT_BRANCH=$(gh pr view "$PARENT" --json headRefName -q .headRefName)
git fetch origin && git rebase "origin/$PARENT_BRANCH"   # pre-flight: sync with the parent
gh pr create --base "$PARENT_BRANCH" --title "$TYPE(#$ISSUE): ... [2/3]" \
  --body "Stacked on #$PARENT. Do not merge into the parent branch."

Phase 1's guard still applies: never open from main or dev, never with a dirty tree. Record git rev-parse "origin/$PARENT_BRANCH" in the body; after the parent is squash-merged that sha is the upstream argument that git rebase --onto "origin/$BASE" <that-sha> <branch> needs, and the branch itself is gone. Squash recovery, depth cap, draft trap: Read("references/stacked-pr.md").


STEP 0: Verify User Intent

BEFORE creating tasks, clarify PR type:

python
AskUserQuestion(
  questions=[{
    "question": "What type of PR is this?",
    "header": "PR Type",
    "options": [
      {"label": "Feature (Recommended)", "description": "Full validation: security + quality + tests"},
      {"label": "Bug fix", "description": "Focus on test verification"},
      {"label": "Refactor", "description": "Code quality review, skip security"},
      {"label": "Quick", "description": "Skip validation, just create PR"}
    ],
    "multiSelect": false
  }]
)

Based on answer, adjust workflow:

  • Feature: Full Phase 2 with 3 parallel agents + local tests
  • Bug fix: Phase 2 with test-generator only + local tests
  • Refactor: Phase 2 with code-quality-reviewer only + local tests
  • Quick: Skip Phase 2, jump to Phase 3

Optional pre-flight: claude ultrareview (CC 2.1.120+, #1542)

If claude ultrareview --help succeeds, optionally run it before opening the PR and surface findings in the PR body's ## Pre-flight section. The CLI subcommand returns structured --json output that can be filtered to high/medium severity for the body and full results posted as a follow-up comment.

bash
if claude ultrareview --help >/dev/null 2>&1; then
  claude ultrareview "origin/$BASE..HEAD" --json > /tmp/ultra.json
  # Bucket by severity, put HIGH in PR body, MEDIUM/LOW as comment
fi

Skip on CC < 2.1.120 (the subcommand doesn't exist there). The .github/workflows/ultrareview.yml workflow runs the same command on PR open as a backstop, so this pre-flight is purely a feedback-loop accelerant.

Progressive Output (CC 2.1.76)

Output results incrementally during PR creation:

After StepShow User
Pre-flightBranch status, remote sync result
Each agentAgent validation result as it returns
TestsTest results, lint/typecheck status
PR createdPR URL, CI status link

For feature PRs with 3 parallel agents, show each agent's result as it returns — don't wait for all agents before running local tests.


STEP 1: Create Tasks (MANDATORY)

BEFORE doing ANYTHING else, create tasks to track progress:

python
# 1. Create main task IMMEDIATELY
TaskCreate(subject="Create PR for {branch}", description="PR creation with validation", activeForm="Creating pull request")

# 2. Create subtasks for each phase
TaskCreate(subject="Pre-flight checks", activeForm="Running pre-flight checks")        # id=2
TaskCreate(subject="Run validation agents", activeForm="Validating with agents")       # id=3
TaskCreate(subject="Run local tests", activeForm="Running local tests")                # id=4
TaskCreate(subject="Create PR on GitHub", activeForm="Creating GitHub PR")             # id=5
TaskCreate(subject="Generate PR playground", activeForm="Generating playground")       # id=6

# 3. Set dependencies for sequential phases
TaskUpdate(taskId="3", addBlockedBy=["2"])  # Agents need pre-flight to pass
TaskUpdate(taskId="4", addBlockedBy=["3"])  # Tests run after agent validation
TaskUpdate(taskId="5", addBlockedBy=["4"])  # PR creation needs tests to pass
TaskUpdate(taskId="6", addBlockedBy=["5"])  # Playground after PR (needs title/summary)

# 4. Update status as you progress
TaskUpdate(taskId="2", status="in_progress")  # When starting
TaskUpdate(taskId="2", status="completed")    # When done — repeat for each subtask

Workflow

Phase 1: Pre-Flight Checks

Load: Read("rules/preflight-validation.md") for the full checklist.

bash
BRANCH=$(git branch --show-current)
[[ "$BRANCH" == "dev" || "$BRANCH" == "main" ]] && echo "Cannot PR from dev/main" && exit 1
[[ -n $(git status --porcelain) ]] && echo "Uncommitted changes" && exit 1

git fetch origin
git rev-parse --verify "origin/$BRANCH" &>/dev/null || git push -u origin "$BRANCH"

Phase 2: Parallel Validation (Feature/Bug fix PRs)

Launch agents in ONE message. Load Read("references/parallel-validation.md") for full agent configs.

PR TypeAgents to launch
Featuresecurity-auditor + test-generator + code-quality-reviewer
Bug fixtest-generator only
Refactorcode-quality-reviewer only
QuickNone

After agents complete, run local validation:

bash
# Adapt to project stack
npm run lint && npm run typecheck && npm test -- --bail
# or: ruff check . && pytest tests/unit/ -v --tb=short -x

Phase 3: Gather Context

bash
BRANCH=$(git branch --show-current)
ISSUE=$(echo "$BRANCH" | grep -oE '[0-9]+' | head -1)
git log --oneline "origin/$BASE..HEAD"
git diff "origin/$BASE...HEAD" --stat

Phase 3b: Agent Attribution (automatic)

Before creating the PR, check for the branch activity ledger at .claude/agents/activity/{branch}.jsonl. If it exists, generate agent attribution sections for the PR body:

  1. Read .claude/agents/activity/{branch}.jsonl (one JSON object per line, full branch history)
  2. Deduplicate by agent type (keep the entry with longest duration for each agent)
  3. Generate the following sections to append to the PR body:
    • Badge row: shields.io badges for agent count, tests generated, vulnerabilities
    • Agent Team Sheet: Markdown table with Agent, Role, Stage (Lead/⚡ Parallel/Follow-up), Time
    • Credits Roll: Collapsible <details> section grouped by execution stage (Lead/Parallel/Follow-up)
  4. Each agent entry has: agent (type), stage (0=lead, 1=parallel, 2=follow-up), duration_ms, summary

If the ledger doesn't exist or is empty, skip this step — create PR normally.

CC 2.1.183 — attribution.sessionUrl: Web and Remote Control sessions append a claude.ai session link to the PR body. For public repos where that link should not be exposed, set attribution.sessionUrl: false (/config attribution.sessionUrl=false) before creating the PR. ork's agent-attribution sections above are independent of this setting.

Phase 3c: CodeRabbit CLI pre-review (before gh pr create)

CodeRabbit PR reviews are rate limited per GitHub identity (Essentials: 5/hour refill under 30 reviews in 7 days, 1/hour at 60+), and every push to an open PR spends one. The CLI has a separate allowance, so review the branch diff locally first. Advisory only, never blocks.

bash
CR_BIN=$(command -v coderabbit || true)   # `cr` is also helm chart-releaser: accept it only by --help
[ -z "$CR_BIN" ] && command -v cr >/dev/null 2>&1 && grep -q CodeRabbit <<<"$(cr --help 2>&1)" && CR_BIN=cr
CR_OUT=$(mktemp "${TMPDIR:-/tmp}/cr-prereview.XXXXXX")
[ -n "$CR_BIN" ] && perl -e 'alarm shift; exec @ARGV' 600 \
  "$CR_BIN" review --agent --base "origin/$BASE" </dev/null > "$CR_OUT" 2>&1 \
  || echo "CodeRabbit CLI pre-review skipped (not installed, not signed in, timed out, or errored): $CR_OUT"

Fix clear defects in lines this branch changed, commit, re-run Phase 2 local validation, then go to Phase 4 without re-running the CLI. Omitting --use-credits avoids spend only when the org's usage-based add-on is On demand or Off; Automatic bills overages. Detection, degrade table, billing modes, triage: Read("references/coderabbit-cli-prereview.md").

Phase 4: Create PR

Follow Read("rules/pr-title-format.md") and Read("rules/pr-body-structure.md"). Use HEREDOC pattern from Read("references/pr-body-templates.md").

Include agent attribution sections (from Phase 3b) after the Test Plan section in the PR body.

bash
TYPE="feat"  # Determine: feat/fix/refactor/docs/test/chore
gh pr create --base "$BASE" \
  --title "$TYPE(#$ISSUE): Brief description" \
  --body "$(cat <<'EOF'
## Summary
[1-2 sentence description]

## Changes
- [Change 1]
- [Change 2]

## Test Plan
- [x] Unit tests pass
- [x] Lint/type checks pass

## Agent Team Sheet
| Agent | Role | Stage | Time |
|-------|------|-------|------|
| 🏗️ **backend-system-architect** | API design | Lead | 2m14s |
| 🛡️ **security-auditor** | Dependency audit | ⚡ Parallel | 0m42s |
| 🧪 **test-generator** | 47 tests, 94% coverage | ⚡ Parallel | 2m01s |

<details>
<summary><strong>🎬 Agent Credits</strong> — 3 agents collaborated on this PR</summary>

**Lead**
- 🏗️ **backend-system-architect** — API design (2m14s)

**⚡ Parallel** (ran simultaneously)
- 🛡️ **security-auditor** — Dependency audit (0m42s)
- 🧪 **test-generator** — 47 tests, 94% coverage (2m01s)

---
<sub>Orchestrated by <a href="https://github.com/yonatangross/orchestkit">OrchestKit</a> — 3 agents, 4m57s total</sub>

</details>

Closes #$ISSUE

---
Generated with [Claude Code](https://claude.com/claude-code)
EOF
)"

Phase 4b: PR Playground (REQUIRED, CI blocks without it)

On every non-bot PR, after Phase 4: Read("references/pr-playground.md") and follow it (archetype, commit to docs/{branch-dir}/, SHA-pinned Live Preview link in the body).

Phase 5: Verify

bash
PR_URL=$(gh pr view --json url -q .url)
echo "PR created: $PR_URL"

CI Monitoring (CC 2.1.71)

After PR creation, schedule CI status monitoring.

Budget: 60 minutes of CI polling (a 5-minute cron, so at most 12 fires). A cron job repeats one fixed prompt and cannot count its own fires, so the prompt carries a wall-clock deadline computed once at creation; stop when every check has finished or at the deadline, whichever comes first, and CronDelete the job at either stop.

python
# Guard: Skip cron in headless/CI (CLAUDE_CODE_DISABLE_CRON)
# if env CLAUDE_CODE_DISABLE_CRON is set, run a single check instead
# deadline_iso = creation time + 60 minutes, in UTC, filled in ONCE here
CronCreate(
  schedule="*/5 * * * *",
  prompt="Check CI for PR #{pr_number}: gh pr checks {pr_number} --repo {repo}. Deadline {deadline_iso}.
    All pass → CronDelete this job, report success.
    Any fail → CronDelete this job, alert with failure details.
    Still pending and `date -u` is at or past the deadline → CronDelete this job, report the pending checks."
)

CodeRabbit harvest

After CI is green and before gh pr merge or --auto, when the repo has .coderabbit.yaml and the PR is not a draft: Read("references/coderabbit-harvest.md").

Handoff File

Write PR details for downstream skills:

python
Write(".claude/chain/pr-created.json", JSON.stringify({
  "phase": "create-pr", "pr_number": N, "pr_url": "...",
  "branch": "...", "files_changed": [...], "related_issues": [...]
}))

Rules

  1. NO junk files — Don't create files in repo root
  2. Run validation locally — Don't spawn agents for lint/test
  3. All content goes to GitHub — PR body via gh pr create --body
  4. Keep it simple — One command to create PR
  5. Respect the gh rate-limit hint (CC ≥ 2.1.116) — when the Bash tool surfaces a GitHub rate-limit hint after a gh call (e.g. in a /loop 5m gh pr checks … watcher), stop the loop and wait for reset — do not blind-retry. See ork:github-operations for the full guidance.

Next Steps (suggest to user after PR creation)

review-pr {PR_NUMBER}                # Self-review before requesting reviews
gh pr checks {PR_NUMBER}                  # one-shot status; the CI Monitoring cron polls up to its 60-minute deadline
/loop 1h gh pr view {PR_NUMBER} --json reviewDecision  # Monitor review status

Verification Gate

Before claiming PR is ready, apply: Read("${CLAUDE_PLUGIN_ROOT}/shared/rules/verification-gate.md"). All tests must pass with fresh evidence. All CI checks green. No "should be fine."

Quality Bar

Done means all of these hold:

  • PR opened from a feature branch with a clean working tree against the correct base ($BASE, derived from origin/HEAD, or the detected host equivalent)
  • Title uses conventional type(#issue): ... format matching the change
  • Body carries Summary, Changes, and Test Plan sections; every closed issue has its own Closes #N keyword
  • Pre-flight validation for the chosen PR type passed locally before creation (skipped only for the Quick type)
  • CodeRabbit CLI pre-review ran once before gh pr create (Phase 3c), or its one-line skip reason is in the Test Plan
  • Playground HTML exists at docs/{branch-dir}/*.html and the body links it, per references/pr-playground.md (required for non-bot PRs)
  • gh pr view --json url returns the created PR URL
  • On repos with .coderabbit.yaml and a non-draft PR: every CodeRabbit thread is resolved per references/coderabbit-harvest.md, with a reply naming the fix sha or the dismissal reason (scripts/coderabbit-harvest.sh --unresolved prints [])

Related Skills

  • ork:commit — Create commits before PRs
  • ork:review-pr — Review PRs after creation

Picker fallback (#1795)

If the AskUserQuestion picker stalls (schema break, not a CC input bug — orchestkit#1795, now guarded by tests/skills/structure/test-askuserquestion-schema.sh), set ORK_ASK_FALLBACK=text before starting CC. The lifecycle/ask-fallback-injector hook injects a reminder telling the assistant to pose options inline as a numbered list and ask the user to reply with the option number.

References

Load on demand with Read("references/<file>"):

FileContent
references/pr-body-templates.mdPR body templates
references/parallel-validation.mdParallel validation agent configs
references/ci-integration.mdCI integration patterns
references/multi-commit-pr.mdMulti-commit PR guidance
assets/pr-template.mdPR template (legacy)
scripts/coderabbit-harvest.shCodeRabbit threads: read (one GraphQL call), --reply, --resolve
references/coderabbit-zero-reviews.mdHarvest returned zero: reviewed clean, or never reviewed?
references/coderabbit-cli-prereview.mdPhase 3c: why the PR review allowance is scarce, CLI command, degrade table, triage
references/pr-playground.mdPhase 4b: PR playground archetype, commit path, SHA-pinned Live Preview link (CI gate)
references/coderabbit-harvest.mdAfter CI green: read, refute, fix or dismiss, resolve every CodeRabbit thread

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Create Pr AI skill do?

Creates GitHub pull requests with pre-flight validation, conventional title formatting, and structured summary generation. Runs parallel checks (tests, lint, type-check, security) before opening. Supports feature, bugfix, refactor, and hotfix PR types with milestone assignment via gh CLI. Invoke only if the operator named it; an everyday `gh pr create` stays plain tooling. Use when opening PRs or submitting code for review.

Why use Create Pr on TypingMind?

Because you install it once and use it with any model. Create Pr is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Create Pr in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yonatangross/orchestkit/tree/main/plugins/ork/skills/create-pr. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Create Pr?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Create Pr?

As many as you like. As long as a model supports skills, you can use Create Pr with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Create Pr AI skill free?

Yes. It is published on GitHub by yonatangross under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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