Analyze Git changes, group related files for staging, and create commits using Conventional Commits, a structured message format. Infer the change type and scope from the diff, with optional user overrides for the type, scope, and description.
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Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Create standardized, semantic git commits using the Conventional Commits specification. Analyze the actual diff to determine appropriate type, scope, and message.
<type>[optional scope]: <description>
[optional body]
[optional footer(s)]
| Type | Purpose |
|---|---|
feat | New feature |
fix | Bug fix |
docs | Documentation only |
style | Formatting/style (no logic) |
refactor | Code refactor (no feature/fix) |
perf | Performance improvement |
test | Add/update tests |
build | Build system/dependencies |
ci | CI/config changes |
chore | Maintenance/misc |
revert | Revert commit |
# Exclamation mark after type/scope
feat!: remove deprecated endpoint
# BREAKING CHANGE footer
feat: allow config to extend other configs
BREAKING CHANGE: `extends` key behavior changed
# If files are staged, use staged diff
git diff --staged
# If nothing staged, use working tree diff
git diff
# Also check status
git status --porcelain
If nothing is staged or you want to group changes differently:
# Stage specific files
git add path/to/file1 path/to/file2
# Stage by pattern
git add *.test.*
git add src/components/*
# Interactive staging
git add -p
Never commit secrets (.env, credentials.json, private keys).
Analyze the diff to determine:
# Single line
git commit -m "<type>[scope]: <description>"
# Multi-line with body/footer
git commit -m "$(cat <<'EOF'
<type>[scope]: <description>
<optional body>
<optional footer>
EOF
)"
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Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.
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Assess a repository’s readiness for AI agents with AgentRC and generate a standalone HTML dashboard. Review scores across nine areas, see prioritized improvements, and optionally apply scoring policies tailored to an organization.
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Generate coding agent instruction files from a project's actual code using AgentRC. Capture detected languages, frameworks, and conventions in one shared file or split rules by topic and project area, with a preview before writing.
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Customize AgentRC readiness assessments to match team or organization standards. Choose or create policies that adjust check importance, disable irrelevant checks, set pass thresholds, and define requirements for automated checks in CI workflows.
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Analyze supplied ad performance data to identify wasted spend, strong campaigns, and next tests. Compare channels, assess whether test differences are meaningful, and produce budget reallocation recommendations with a prioritized action plan.
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Turn code files into learning resources by adding comments that explain syntax, programming concepts, and design choices. Adjust explanation depth and repetition to the reader’s knowledge while preserving file structure, encoding, and syntax.
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