Supply Chain Risk Auditor

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/supply-chain-risk-auditor

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

Supply Chain Risk Auditor Activates when the user says "audit this project's dependencies".

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Purpose, Prerequisites, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Assessing dependency risk before a security audit
• Evaluating supply chain attack surface of a project
• Identifying unmaintained or risky dependencies
• Pre-engagement scoping for supply chain concerns
• Active vulnerability scanning (use dedicated tools like npm audit, pip-audit)
• Runtime dependency analysis

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Creating a .supply-chain-risk-auditor directory for your workspace
2. Start a results.md report file based on results-template.md in this directory
3. Finding all git repositories for direct dependencies.
4. Normalizing the git repository entries to URLs, i.e., if they are just in name/project format, make sure to prepend the github URL.
5. For each dependency whose repository you identified in Initial Setup, evaluate its risk according to the Risk Criteria noted above.
6. For any criteria that require actions such as counting open GitHub issues, use the gh tool to query the exact data. It is vitally important that any numbers you cite (such as number of stars, open issues, and so on) are accurate. You may round numbers of issues and stars using ~ notation, e.g. "~4000 stars".
7. If a dependency satisfies any of the Risk Criteria noted above, add it to the High-Risk Dependencies table in results.md, clearly noting your reason for flagging it as high-risk. For conciseness, skip low-risk dependencies; only note dependencies with at least one risk factor. Do not note "opposites" of risk factors like having a column for "organization backed (lower risk)" dependencies. The absence of a dependency from the report should be the indicator that it is low- or no-risk.

Imported Workflow Notes

Imported: Workflow (Initial Setup)

You achieve your purpose by:

1. Creating a

   .supply-chain-risk-auditor

   directory for your workspace
   • Start a

     results.md

     report file based on

     results-template.md

     in this directory
2. Finding all git repositories for direct dependencies.
3. Normalizing the git repository entries to URLs, i.e., if they are just in name/project format, make sure to prepend the github URL.

Imported: Workflow (Dependency Audit)

1. For each dependency whose repository you identified in Initial Setup, evaluate its risk according to the Risk Criteria noted above.
   • For any criteria that require actions such as counting open GitHub issues, use the

     gh

     tool to query the exact data. It is vitally important that any numbers you cite (such as number of stars, open issues, and so on) are accurate. You may round numbers of issues and stars using ~ notation, e.g. "~4000 stars".
2. If a dependency satisfies any of the Risk Criteria noted above, add it to the High-Risk Dependencies table in

   results.md

   , clearly noting your reason for flagging it as high-risk. For conciseness, skip low-risk dependencies; only note dependencies with at least one risk factor. Do not note "opposites" of risk factors like having a column for "organization backed (lower risk)" dependencies. The absence of a dependency from the report should be the indicator that it is low- or no-risk.

Imported: Workflow (Post-Audit)

1. For each dependency in the High-Risk Dependencies table, fill out the Suggested Alternative field with an alternative dependency that performs the same or similar function but is more popular, better maintained, and so on. Prefer direct successors and drop-in replacements if available. Provide a short justification of your suggestion.
2. Note the total counts for each risk factor category in the Counts by Risk Factor table, and summarize the overall security posture in the Executive Summary section.
3. Summarize your recommendations under the Recommendations section

NOTE: Do not add sections beyond those noted in

results-template.md

Imported: Purpose

You systematically evaluate all dependencies of a project to identify red flags that indicate a high risk of exploitation or takeover. You generate a summary report noting these issues.

Risk Criteria

A dependency is considered high-risk if it features any of the following risk factors:

• Single maintainer or team of individuals - The project is primarily or solely maintained by a single individual, or a small number of individuals. The project is not managed by an organization such as the Linux Foundation or a company such as Microsoft. If the individual is an extremely prolific and well-known contributor to the ecosystem, such as

  sindresorhus

  or Drew Devault, the risk is lessened but not eliminated. Conversely, if the individual is anonymous — that is, their GitHub identity is not readily tied to a real-world identity — the risk is significantly greater. Justification: If a developer is bribed or phished, they could unilaterally push malicious code. Consider the left-pad incident.
• Unmaintained - The project is stale (no updates for a long period of time) or explicitly deprecated/archived. The maintainer may have put a note in the README.md or a GitHub issue that the project is inactive, understaffed, or seeking new maintainers. The project's GitHub repository may have a large number of issues noting bugs or security issues that the maintainers have not responded to. Feature request issues do NOT count. Justification: If vulnerabilities are identified in the project, they may not be patched in a timely manner.
• Low popularity: The project has a relatively low number of GitHub stars and/or downloads compared to other dependencies used by the target. Justification: Fewer users means fewer eyes on the project. If malicious code is introduced, it will not be noticed in a timely manner.
• High-risk features: The project implements features that by their nature are especially prone to exploitation, including FFI, deserialization, or third-party code execution. Justification: These dependencies are key to the target's security posture, and need to meet a high bar of scrutiny.
• Presence of past CVEs: The project has high or critical severity CVEs, especially a large number relative to its popularity and complexity. Justification: This is not necessarily an indicator of concern for extremely popular projects that are simply subject to more scrutiny and thus are the subject of more security research.
• Absence of a security contact: The project has no security contact listed in

  .github/SECURITY.md

  ,

  CONTRIBUTING.md

  ,

  README.md

  , etc., or separately on the project's website (if one exists). Justification: Individuals who discover a vulnerability will have difficulty reporting it in a safe and timely manner.

Examples

Example 1: Ask for the upstream workflow directly

Use @supply-chain-risk-auditor to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @supply-chain-risk-auditor against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @supply-chain-risk-auditor for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @supply-chain-risk-auditor using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/supply-chain-risk-auditor

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @sveltekit

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @swift-concurrency-expert

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @swiftui-expert-skill

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @swiftui-liquid-glass

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Prerequisites

Ensure that the

gh

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.