push-to-registry

hashicorp/agent-skills · updated Apr 8, 2026

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$npx skills add https://github.com/hashicorp/agent-skills --skill push-to-registry
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summary

Push Packer build metadata to HCP Packer registry for image lifecycle tracking and governance.

  • 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
skill.md

Push to HCP Packer Registry

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).

Basic Registry Configuration

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",
    ]
  }
}

Authentication

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 .

Create HCP Service Principal

  1. Navigate to HCP → Access Control (IAM)
  2. Create Service Principal
  3. Grant "Contributor" role on project
  4. Generate client secret
  5. Save client ID and secret

Registry Configuration Options

bucket_name (required)

The image identifier. Must stay consistent across builds!

bucket_name = "web-server"  # Keep this constant

bucket_labels (optional)

Metadata at bucket level. Updates with each build.

bucket_labels = {
  "os"        = "ubuntu"
  "team"      = "platform"
  "component" = "web"
}

build_labels (optional)

Metadata for each iteration. Immutable after build completes.

build_labels = {
  "build-time" = local.timestamp
  "git-commit" = var.git_commit
}

CI/CD Integration

GitHub Actions

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 }}" \
            .

Querying in Terraform

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
  }
}

Common Issues

Authentication Failed

  • Verify HCP_CLIENT_ID and HCP_CLIENT_SECRET
  • Ensure service principal has Contributor role
  • Check organization and project IDs

Bucket Name Mismatch

  • Keep bucket_name consistent across builds
  • Don't include timestamps in bucket_name
  • Creates new bucket if name changes

Build Fails

  • Packer fails immediately if can't push metadata
  • Prevents drift between artifacts and registry
  • Check network connectivity to HCP API

Best Practices

  • Consistent bucket names - Never change for same image type
  • Meaningful labels - Use for versions, teams, compliance
  • CI/CD automation - Automate builds and registry pushes
  • Immutable build labels - Put changing data (git SHA, date) in build_labels

References

how to use push-to-registry

How to use push-to-registry on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add push-to-registry
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/hashicorp/agent-skills --skill push-to-registry

The skills CLI fetches push-to-registry from GitHub repository hashicorp/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/push-to-registry

Reload or restart Cursor to activate push-to-registry. Access the skill through slash commands (e.g., /push-to-registry) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.653 reviews
  • Pratham Ware· Dec 28, 2024

    Keeps context tight: push-to-registry is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Soo Kapoor· Dec 28, 2024

    Solid pick for teams standardizing on skills: push-to-registry is focused, and the summary matches what you get after install.

  • William Brown· Dec 24, 2024

    We added push-to-registry from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chaitanya Patil· Dec 20, 2024

    push-to-registry reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Emma Harris· Dec 20, 2024

    push-to-registry fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ira Li· Dec 8, 2024

    push-to-registry has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ishan Haddad· Nov 27, 2024

    push-to-registry fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Kaira Sharma· Nov 19, 2024

    We added push-to-registry from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Amelia Thomas· Nov 15, 2024

    Solid pick for teams standardizing on skills: push-to-registry is focused, and the summary matches what you get after install.

  • Piyush G· Nov 11, 2024

    I recommend push-to-registry for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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