pr-create
Skill1 starsChanged 2 months agoMITView on GitHub
Create a pull request with auto-generated description. Summarizes changes and generates PR body via local LLM (llm:think), then creates the PR after user approval. Use this skill when: asked to create a PR; asked to submit changes for review; asked to open a pull request.
- Commits and pushes
26 other projects use a version of this.
Adopted by
Most recently taken up by
- AloisSeckar/demos-javatheir own version, first seen Nov 9, 2026
- BrightGold70/skillstheir own version, first seen Nov 8, 2026
- mmurakaru/skillstheir own version, first seen Nov 6, 2026
- kanopi/cms-cultivatortheir own version, first seen Nov 1, 2026
- Hakkadaikon/hymmetheir own version, first seen Oct 26, 2026
- matthull/my-skillstheir own version, first seen Oct 20, 2026
Used with
Projects with it also use pr-feedback, commit and 1 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
dversozaSkillpr-feedback
Address PR review feedback including inline threads, general comments, bot-generated reviews, PR description findings, check run annotations (inline lint/type/security findings shown in the Files changed tab), code scanning alerts, and CI failures. Use when asked to handle, address, resolve, respond to, or work through PR review comments, review feedback, inline findings, or CI check failures. Triggers on requests like "address PR comments", "handle review feedback", "resolve PR reviews", "fix review comments", "go through PR feedback", "check CI failures", "fix the inline findings on the PR".
Also in 5 projects that use this
SentrySkillcommit
Create commit messages following Sentry conventions. Use when committing code changes, writing commit messages, or formatting git history. Follows conventional commits with Sentry-specific issue references.
Also in 5 projects that use this
GoogleSkillcode-review
Adversarial systems, concurrency, memory-model, and architecture code review protocol. Use this skill whenever asked to review code, PRs, diffs, or branches in Filament.
Also in 3 projects that use this
Other versions26 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 26
- strands-agents/sdk-python★ 9.1ksame name
- strands-agents/harness-sdk★ 8.9ksame name
- basicmachines-co/basic-memory★ 4.5ksame name
- idaholab/moose★ 2.4ksame name
- AloisSeckar/demos-java★ 25same name
- genlayerlabs/skills★ 19same name
- kanopi/cms-cultivator★ 17same name
- yasunori0418/skills★ 9same name
- BenjaminG/ai-skills★ 4same name
- hartleybrody/.agent-skills★ 4same name
16 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository10 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- global/CLAUDE.mdCLAUDE.md
- agent-reviewSkill
- context-budgetSkill
- exploreSkill
- retrospectSkill
- security-scanSkill
- simplifySkill
- test-genSkill
- triangulateSkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 23 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 29
If on main branch, ask the user for the target branch or create one.
- Distinctive: line 31
Ensure all changes are committed before proceeding.
- Distinctive: line 51
If Ollama is unavailable, proceed to Step 3 without pre-analysis.
- Distinctive: line 74
If Ollama is unavailable, compose the PR body directly as fallback.
- Distinctive: line 89
After user approval (allow editing the title and body):
“Common” is measured: kept by at least 6 in 10 of the 23 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
PR Create Skill
Creates a pull request with an auto-generated description using local LLM for summarization and PR body composition.
Step 1: Gather Context (Shell Only, Zero Claude Tokens)
# Confirm branch and ensure not on main
git branch --show-current
# Get change summary
git diff main...HEAD --stat
# Get commit history
git log main...HEAD --oneline
# Check for review artifacts (plan, review log, deviation log, code review log)
ls ./docs/archive/review/*-plan.md ./docs/archive/review/*-review.md \
./docs/archive/review/*-deviation.md ./docs/archive/review/*-code-review.md 2>/dev/nullIf on main branch, ask the user for the target branch or create one.
Ensure all changes are committed before proceeding.
Step 2: Local LLM Analysis (Zero Claude Tokens)
Summarize changes, classify the PR type, and pre-generate a title:
# Summarize the diff
SUMMARY=$(git diff main...HEAD | bash ~/.claude/hooks/llm-commands.sh summarize-diff)
# Classify changes
CATEGORY=$(git diff main...HEAD --name-only | bash ~/.claude/hooks/llm-commands.sh classify-changes)
# Generate a draft title from category + summary
TITLE=$({ echo "$CATEGORY"; echo '=== OLLAMA-INPUT-SEPARATOR ==='; echo "$SUMMARY"; } \
| bash ~/.claude/hooks/llm-commands.sh generate-pr-title)
printf '%s\n' "$SUMMARY" "$CATEGORY" "$TITLE"If Ollama is unavailable, proceed to Step 3 without pre-analysis.
Step 3: Local LLM PR Body Generation (Zero Claude Tokens)
# Aggregate context for generate-pr-body: everything on stdin as one section.
{
echo "=== COMMIT LOG ==="
git log main...HEAD --oneline
echo
echo "=== DIFF STAT ==="
git diff main...HEAD --stat
echo
for f in ./docs/archive/review/*-plan.md ./docs/archive/review/*-review.md \
./docs/archive/review/*-deviation.md ./docs/archive/review/*-code-review.md; do
[ -f "$f" ] || continue
echo "=== $f ==="
cat "$f"
echo
done
} | bash ~/.claude/hooks/llm-commands.sh generate-pr-bodyIf Ollama is unavailable, compose the PR body directly as fallback.
Step 4: Review, Approve, and Create
Present the draft PR to the user:
=== PR Draft ===
Title: [TITLE from Step 2, or a short title from change type + summary if Ollama was unavailable]
Base: main
Head: [current branch]
[PR body]After user approval (allow editing the title and body):
gh pr create --title "[title]" --body "$(cat <<'EOF'
[PR body]
EOF
)"Report the PR URL to the user.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

