Release Branch logo

Release Branch

Community
danielvm-git
release-branch

Make the merge/PR/keep/discard decision for a feature branch, verify coverage gates, create the PR with gh, and clean up the worktree. Use when a feature is done and ready to ship, or when user says "release", "merge", or "open a PR".

Overview

Publisherdanielvm-git
Repositorybigpowers
Skill namerelease-branch
Stars
206
Forks
18
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by danielvm-git on GitHub. Read the source before you install it.

Installation

Install the Release Branch 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.
  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/danielvm-git/bigpowers.git /tmp/bigpowers
mkdir -p .claude/skills
cp -r /tmp/bigpowers/skills/release-branch .claude/skills/release-branch
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Release Branch 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 Release Branch 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 Release Branch 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.

Release Branch

HARD GATE — Do NOT merge or release if tests fail or if coverage gates are not met. If the branch is red, return to develop-tdd to fix regressions or add missing tests before proceeding.

Finalize a completed feature branch: verify coverage gates, integrate onto main, and clean up the worktree.

Additional modes

  • --hotfix: Cherry-pick to main + tag. Skip PR in solo.
  • --squash-state: Squash chore(state): commits before merge.

Integrate mode

Read specs/state.yaml key workflow_mode (team-pr | solo-git). Fall back to profiles/solo-git.md.

ModeWhenShip path
solo-localworkflow_mode: solo-gitAuto: scripts/land-branch.sh if present, else fallback (Step 5)
team-prworkflow_mode: team-pr (default)gh pr creategh pr merge --squash

If unsure, prefer solo-local. Also read state.yaml vcs.kind: Git follows the procedures below; Jujutsu uses workspaces/bookmarks and must not call Git-only landing scripts.

Process

Timing: bash scripts/bp-timing.sh start release-branch at invocation; bash scripts/bp-timing.sh end release-branch before handoff.

1. Final verification

bash
<full test command> && <typecheck command> && <lint command>
git log main...HEAD --oneline | grep -vE "^[a-f0-9]+ (feat|fix|docs|style|refactor|perf|test|build|ci|chore|revert)(\(.+\))?!?: .+$" && echo "❌ Non-conventional commits found" || echo "✅ Commits verified"
# Block AI agent attribution (P1)
git log main...HEAD --format="%B" | grep -qiE 'co[- ]authored[- ]by' && echo "❌ Co-authored-by footer found — blocked" || echo "✅ No AI attribution"
  • All tests pass, no type errors, no lint violations, all commits follow Conventional Commits
  • NO Co-authored-by or Co-Authored-By in any commit body — P1 rule (CONVENTIONS.md § Git Attribution). land-branch.sh blocks the merge if found.

2. Coverage check

  • Overall coverage ≥ 80%; business logic coverage ≥ 95%

2a. Security gate

  • specs/security/REVIEW.md exists and is fresh (matches current branch diff)
  • No unresolved HIGH findings with confidence ≥ 8 (or all documented in specs/security/EXCEPTIONS.md with sign-off rationale)

If REVIEW.md is missing or stale → run security-review inline. Findings block the merge unless documented in EXCEPTIONS.md.

2b. Traceability gate

Run gate-trace before merge. FAIL blocks merge; CONCERNS requires explicit override in specs/state.yaml (traceability_override: CONCERNS accepted, reason: <explanation>). WAIVED if no matrix available.

Adversarial refute framing (e45s32): The final pre-merge check is refute, not rubber-stamp. Before declaring ready, actively try to disprove traceability completeness — missing story tags, absent verify evidence, stale security review. Only proceed when refutation fails.

3. Diff review

  • All commits intentional, no secrets, CONVENTIONS.md compliance

4. Decision

Options: Release (solo-local) / Open PR / Keep branch / Discard

5. Integrate

Run commit-message first. Git solo-local uses land-branch.sh. Jujutsu team mode explicitly advances and pushes a bookmark; -m is mandatory for commit/describe operations:

bash
# Git solo-local
bash scripts/land-branch.sh <task-slug> "feat(scope): description"
# Jujutsu team PR
jj describe -m "feat(scope): description"
jj bookmark set <task-slug> -r @
jj git push -b <task-slug>

Jujutsu solo-local landing is unsupported: run bp_require_vcs_operation "$PWD" land-branch and stop with its remediation instead of invoking the Git backend.

6. Create PR (team-pr only)

Create the pull request with a literal provenance marker in the body so agent-generated PRs are identifiable and do not rot silently:

markdown
<!-- bigpowers-provenance: agent-generated -->

Place the marker on its own line immediately after the ## Summary heading. Then merge via gh:

bash
gh pr create --title "..." --body "$(cat <<'EOF'
## Summary
<!-- bigpowers-provenance: agent-generated -->

- ...

## Test plan
- [ ] ...

EOF
)"
gh pr merge --squash --delete-branch

semantic-release auto-detects the commit, bumps SemVer, tags the repo, generates release notes.

7a. Archive completed epic capsule

HARD GATE — When all epic stories are done (all done in execution-status.yaml), archive the capsule:

bash
mv specs/epics/eNN-slug specs/epics/archive/

7b. CI verification & agent lock release (e39s02)

HARD GATE — Do NOT declare success until CI completes. Three-independent-facts (e45s15): commit landed, workflow green, registry visible — see REFERENCE.md.

bash
bash scripts/wait-for-ci.sh --timeout 600 --interval 30
  • CI passes; release.ci_verified: true in state.yaml
  • On failure: handoff.next_skill = fix-bug

8. Clean up & return

Git: prune worktree, delete branch, return to main. Jujutsu: jj workspace forget <workspace> only after integration; do not delete its bookmark implicitly. Cycle-time: see REFERENCE.md.

Report: "Branch released."

Verify

→ verify: command -v gh >/dev/null 2>&1 && test -f specs/state.yaml && test -d skills/verify-work

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 Release Branch AI skill do?

Make the merge/PR/keep/discard decision for a feature branch, verify coverage gates, create the PR with gh, and clean up the worktree. Use when a feature is done and ready to ship, or when user says "release", "merge", or "open a PR".

Why use Release Branch on TypingMind?

Because you install it once and use it with any model. Release Branch 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 Release Branch in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/danielvm-git/bigpowers/tree/main/skills/release-branch. 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 Release Branch?

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 Release Branch?

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

Is the Release Branch AI skill free?

Yes. It is published on GitHub by danielvm-git 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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