Push Packer build metadata to HCP Packer registry for image lifecycle tracking and governance.
Works with
Registers build artifacts in HCP Packer with minimal overhead, storing metadata only (not actual images) and adding less than one minute to build time
Supports bucket-level labels (updated per build) and immutable build-level labels (git SHA, timestamps) for version control and compliance tracking
Integrates with Terraform via hcp_packer_artifact data source to query and deploy images acros
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpush-to-registryExecute the skills CLI command in your project's root directory to begin installation:
Fetches push-to-registry from hashicorp/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate push-to-registry. Access via /push-to-registry in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Configure Packer templates to push build metadata to HCP Packer registry.
Reference: HCP Packer Registry
Note: HCP Packer is free for basic use. Builds push metadata only (not actual images), adding minimal overhead (<1 minute).
packer {
required_version = ">= 1.7.7"
}
variable "image_name" {
type = string
default = "web-server"
}
locals {
timestamp = regex_replace(timestamp(), "[- TZ:]", "")
}
source "amazon-ebs" "ubuntu" {
region = "us-west-2"
instance_type = "t3.micro"
source_ami_filter {
filters = {
name = "ubuntu/images/*ubuntu-jammy-22.04-amd64-server-*"
}
most_recent = true
owners = ["099720109477"]
}
ssh_username = "ubuntu"
ami_name = "${var.image_name}-${local.timestamp}"
}
build {
sources = ["source.amazon-ebs.ubuntu"]
hcp_packer_registry {
bucket_name = var.image_name
description = "Ubuntu 22.04 base image for web servers"
bucket_labels = {
"os" = "ubuntu"
"team" = "platform"
}
build_labels = {
"build-time" = local.timestamp
}
}
provisioner "shell" {
inline = [
"sudo apt-get update",
"sudo apt-get upgrade -y",
]
}
}
Set environment variables before building:
export HCP_CLIENT_ID="your-service-principal-client-id"
export HCP_CLIENT_SECRET="your-service-principal-secret"
export HCP_ORGANIZATION_ID="your-org-id"
export HCP_PROJECT_ID="your-project-id"
packer build .
The image identifier. Must stay consistent across builds!
bucket_name = "web-server" # Keep this constant
Metadata at bucket level. Updates with each build.
bucket_labels = {
"os" = "ubuntu"
"team" = "platform"
"component" = "web"
}
Metadata for each iteration. Immutable after build completes.
build_labels = {
"build-time" = local.timestamp
"git-commit" = var.git_commit
}
name: Build and Push to HCP Packer
on:
push:
branches: [main]
env:
HCP_CLIENT_ID: ${{ secrets.HCP_CLIENT_ID }}
HCP_CLIENT_SECRET: ${{ secrets.HCP_CLIENT_SECRET }}
HCP_ORGANIZATION_ID: ${{ secrets.HCP_ORGANIZATION_ID }}
HCP_PROJECT_ID: ${{ secrets.HCP_PROJECT_ID }}
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: hashicorp/setup-packer@main
- name: Build and push
run: |
packer init .
packer build \
-var "git_commit=${{ github.sha }}" \
.
data "hcp_packer_artifact" "ubuntu" {
bucket_name = "web-server"
channel_name = "production"
platform = "aws"
region = "us-west-2"
}
resource "aws_instance" "web" {
ami = data.hcp_packer_artifact.ubuntu.external_identifier
instance_type = "t3.micro"
tags = {
PackerBucket = data.hcp_packer_artifact.ubuntu.bucket_name
}
}
Authentication Failed
Bucket Name Mismatch
bucket_name consistent across buildsBuild Fails
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Keeps context tight: push-to-registry is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: push-to-registry is focused, and the summary matches what you get after install.
We added push-to-registry from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
push-to-registry reduced setup friction for our internal harness; good balance of opinion and flexibility.
push-to-registry fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
push-to-registry has been reliable in day-to-day use. Documentation quality is above average for community skills.
push-to-registry fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added push-to-registry from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: push-to-registry is focused, and the summary matches what you get after install.
I recommend push-to-registry for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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