Agent skill

Cve Intelligence Gathering

by openshift-eng in openshift-eng/ai-helpers

Gather comprehensive vulnerability information from multiple authoritative sources with fallback strategies

Apache-2.0Auto-check passedSecurity

Install Cve Intelligence Gathering

skills CLI
$ npx skills add openshift-eng/ai-helpers --skill cve-intelligence-gathering -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install openshift-eng/ai-helpers cve-intelligence-gathering --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/openshift-eng/ai-helpers.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/compliance/skills/cve-intelligence-gathering .claude/skills/cve-intelligence-gathering && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cve-intelligence-gathering
GitHub stars
120
Token cost
~4.1k tokens
SKILL.md length
1,195 words
Files
1
Skills in repo
118
Repo updated
First seen
Licence
Apache-2.0

At a glance

Gather comprehensive vulnerability information from multiple authoritative sources with fallback strategies

  • Works in 9 steps: Validate CVE Format → 5: Seed Profile from Jira Context (if… → Search Primary Sources (NVD and MITRE) → …
  • Tasks that involve Vulnerability scanning
  • SKILL.md covers When to Use This Skill, Prerequisites, Implementation Steps and Return Value, plus 3 more sections
  • Reaches redhat.atlassian.net and nvd.nist.gov

What it does

Cve Intelligence Gathering is an agent skill from openshift-eng/ai-helpers. Gather comprehensive vulnerability information from multiple authoritative sources with fallback strategies

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Security, covering Vulnerability scanning. It works with Jira. The repository describes itself as: Developer productivity tools for Claude Code & other AI assistants. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Vulnerability scanning

Example prompts

  • “/cve-intelligence-gathering”

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Validate CVE Format
  2. 5: Seed Profile from Jira Context (if available)
  3. Search Primary Sources (NVD and MITRE)
  4. Search Go-Specific Sources
  5. Search for Remediation Intelligence
  6. Handle Search Failures and Limited Results
  7. Request User Input (Fallback)
  8. Compile Merged Vulnerability Profile
  9. Determine Go Relevance

What it can do on your machine

Read from SKILL.md and the folder at commit a627176. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • redhat.atlassian.net
    • nvd.nist.gov
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cve Intelligence Gathering loads about 4.1k tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 1,195 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from openshift-eng/ai-helpers at commit a627176, republished under its Apache-2.0 licence (© openshift-eng). 1,195 words, ~4,053 tokens.

Download SKILL.mdSave it as .claude/skills/cve-intelligence-gathering/SKILL.md (or your agent's skills folder).
name
cve-intelligence-gathering
description
Gather comprehensive vulnerability information from multiple authoritative sources with fallback strategies

CVE Intelligence Gathering

Systematically collects CVE vulnerability details from multiple authoritative sources, handles search failures, and compiles a comprehensive vulnerability profile for analysis.

When to Use This Skill

Use this skill when:

  • Starting CVE analysis and need complete vulnerability information
  • Web searches are returning limited or no results
  • CVE is very new and not yet in all databases
  • Need to distinguish between authoritative and user-provided information
  • Building evidence for security compliance reports

Prerequisites

Required
  • Valid CVE identifier (format: CVE-YYYY-NNNNN)
  • Internet connectivity (recommended but not required)
  • web_search tool access
Optional
  • User-provided CVE details (fallback when internet unavailable)
  • Links to security advisories

Implementation Steps

Step 1: Validate CVE Format
bash
# Regex pattern for CVE ID
CVE_PATTERN="^CVE-[0-9]{4}-[0-9]{4,}$"

# Validate format
if [[ "$CVE_ID" =~ $CVE_PATTERN ]]; then
  echo "Valid CVE format"
else
  echo "ERROR: Invalid CVE format. Expected: CVE-YYYY-NNNNN"
  exit 1
fi

Extract components:

  • Year: YYYY from CVE-YYYY-NNNNN
  • Number: NNNNN from CVE-YYYY-NNNNN

Decision Point:

  • IF invalid format → Return error to parent command
  • IF valid → Continue to Step 1.5
Step 1.5: Seed Profile from Jira Context (if available)

If a jira_context object was passed in from the jira-cve-extraction skill (i.e. the parent command was invoked with --jira= or --jql=), pre-populate the vulnerability profile before any web searches. This reduces redundant lookups and surfaces internal context that is not available in public databases.

Fields to extract and pre-populate:

Jira fieldProfile fieldNotes
cvss_score + cvss_vectorseverity.cvss_score, severity.cvss_vectorPrefer Jira value; verify against NVD in Step 2
cwe_idcwe_idCross-check with NVD; flag if they differ
summary (parsed description)description (supplement)Internal phrasing may be more specific
affects_versionsAnalysis scope (which project/release versions are affected)
target_versionsFix target / release window
release_note_textremediation.recommended_action (supplement)May already describe the fix or upgrade path
components, labelsContext only
Description body (workaround scan)remediation.workaroundsAlready extracted by jira-cve-extraction
Internal notes from descriptioninternal_context field in profileCapture any previous analysis, conclusions, or decisions noted in the ticket body

Mark each pre-populated field as source: jira in the profile.

Conflict resolution: If Jira and a public source (NVD, GHSA) disagree on CVSS score or CWE:

  • Note both values in the profile
  • Prefer the higher CVSS score for risk assessment (conservative)
  • Flag the discrepancy as a gap

Decision Point:

  • IF jira_context is null or absent (direct <CVE-ID> mode) → Skip this step entirely, proceed to Step 2 as normal
  • IF jira_context is present → Pre-populate, then continue to Step 2 to fill remaining gaps and verify
Step 2: Search Primary Sources (NVD and MITRE)

National Vulnerability Database (NVD)

text
Search query: "CVE-{ID} site:nvd.nist.gov"
Example: "CVE-YYYY-NNNNN site:nvd.nist.gov"

Extract from results:

  • CVSS Score (v3.1, v3.0, or v2.0)
  • Severity rating (CRITICAL/HIGH/MEDIUM/LOW)
  • Base score and vector string
  • Affected product/versions
  • CWE (Common Weakness Enumeration) ID
  • Published date and last modified date

MITRE CVE Database

text
Search query: "CVE-{ID} site:cve.mitre.org"
Example: "CVE-YYYY-NNNNN site:cve.mitre.org"

Extract from results:

  • CVE description (official)
  • References (links to advisories, patches, exploits)
  • CWE classification
  • Assigning CNA (CVE Numbering Authority)

Error Handling:

  • IF no results from NVD → Try MITRE
  • IF no results from MITRE → Try NVD alternative URL pattern
  • IF both fail → Continue to Step 3 (Go-specific sources)
Step 3: Search Go-Specific Sources

Go Vulnerability Database

text
Search queries:
1. "CVE-{ID} golang vulnerability"
2. "CVE-{ID} site:github.com/golang/vulndb"
3. "CVE-{ID} site:go.dev/security"

Extract from results:

  • Affected Go package/module (e.g., <package-path>)
  • Vulnerable version ranges (e.g., < <version>)
  • Fixed version (e.g., <version>)
  • Vulnerable functions/symbols
  • Import paths

GitHub Security Advisories (GHSA)

text
Search queries:
1. "CVE-{ID} golang GHSA"
2. "CVE-{ID} site:github.com/advisories"

Look for:

  • GHSA identifier (e.g., GHSA-xxxx-xxxx-xxxx)
  • Severity from GitHub
  • Affected versions
  • Patched versions
  • Workarounds if available

Decision Point:

  • IF Go-specific info found → High confidence this is Go-related
  • IF only general CVE info found → May not be Go-specific, note this
  • IF nothing found → Proceed to Step 4
Step 4: Search for Remediation Intelligence

Security Advisories

text
Search queries:
1. "CVE-{ID} security advisory"
2. "CVE-{ID} golang fix"
3. "CVE-{ID} patch"

Look for:

  • Official vendor security bulletins
  • Fix commits on GitHub
  • Release notes mentioning the CVE
  • Migration guides for breaking changes

Community Discussions

text
Search queries:
1. "CVE-{ID} golang github issue"
2. "CVE-{ID} golang discussion"

Check for:

  • GitHub issues discussing the vulnerability
  • Pull requests with fixes
  • Community workarounds
  • Discussion on golang-nuts or Reddit

Proof of Concept / Exploits (for context only)

text
Search query: "CVE-{ID} exploit poc"

Note: Only use for understanding attack vectors, not for testing

Step 5: Handle Search Failures and Limited Results

If CVE is Very New (e.g., published recently)

text
Search alternative queries:
1. "CVE-{ID} disclosure"
2. "CVE-{ID} advisory {YEAR}"
3. "{PACKAGE_NAME} vulnerability {YEAR}"
  • It may not be listed in the NVD yet (this can take weeks)
  • Check vendor security pages directly
  • Look for embargo lift dates
  • Note: govulncheck may have it via GHSA before NVD

If Web Searches Return No Results

Try alternative strategies:

  1. Search by package name (if known from context):

    Search: "{package-name} vulnerability {year}"
    Example: "<package-name> vulnerability <year>"
  2. Search for GHSA aliases:

    Search: "GHSA-{pattern} golang"
  3. Check package repository directly:

    Search: "site:github.com/{org}/{repo} security"

Decision Point:

  • IF still no results → Proceed to Step 6 (User Input)
  • IF partial results → Continue with available data, mark gaps
Show full SKILL.md (492 more words)Show less
Step 6: Request User Input (Fallback)

If automated searches fail: IF AUTO_APPROVE=yes → there is no one to prompt; skip straight to "User Response Handling: no" below (return an error to the parent command). This step is never gated to proceed automatically — fabricating CVE details is not a safe default, regardless of how much unattended automation the caller wants. IF AUTO_APPROVE=no (or unset — the default) → prompt user:

text
❌ Unable to fetch details for {CVE-ID} from online sources.

Attempted searches:
- NVD: No results
- MITRE: No results  
- Go vulnerability database: No results
- GitHub Security Advisories: No results

Please provide any information you have about this CVE:

1. CVE Description:
   [What vulnerability does this CVE describe?]

2. Affected Go Packages/Modules:
   [e.g., <package-path>, github.com/<org>/<repo>]

3. Vulnerable Version Range:
   [e.g., all versions before <version>, or versions <version-range>]

4. Fixed Version (if known):
   [e.g., <version> or later]

5. Severity (if known):
   [CRITICAL/HIGH/MEDIUM/LOW or CVSS score]

6. References (if any):
   [Links to security advisories, GitHub issues, etc.]

You can provide partial information. Analysis will proceed with whatever details are available.

Would you like to provide CVE details? (yes/no)

User Response Handling:

  • IF yes → Collect information, mark as "User-provided"
  • IF no → Return error to parent command (insufficient data to proceed)
Step 7: Compile Merged Vulnerability Profile

Merge all gathered information — Jira context (Step 1.5, if present) and public sources (Steps 2–6) — into a single profile. Every field records which source(s) populated it.

json
{
  "cve_id": "CVE-YYYY-NNNNN",
  "aliases": ["GHSA-xxxx-xxxx-xxxx"],
  "severity": {
    "rating": "<CRITICAL|HIGH|MEDIUM|LOW>",
    "cvss_score": "<score>",
    "cvss_vector": "<CVSS vector string>",
    "cvss_source": "<jira|nvd|ghsa — which source this came from>"
  },
  "affected_packages": [
    {
      "name": "<package-name>",
      "vulnerable_versions": "<version-range>",
      "fixed_version": "<fixed-version>",
      "vulnerable_functions": ["<function1>", "<function2>"]
    }
  ],
  "vulnerability_type": "<vulnerability-type>",
  "cwe_id": "CWE-<number>",
  "attack_vector": "<attack-vector>",
  "description": "<vulnerability description>",
  "impact": {
    "confidentiality": "<NONE|LOW|HIGH>",
    "integrity": "<NONE|LOW|HIGH>", 
    "availability": "<NONE|LOW|HIGH>"
  },
  "remediation": {
    "fix_available": true,
    "recommended_action": "<remediation guidance>",
    "workarounds": ["<workaround from Jira description or public advisory>"],
    "fix_target_versions": ["<target versions from Jira target_versions, if any>"],
    "release_note": "<from Jira release_note_text if present>"
  },
  "internal_context": {
    "jira_ticket": "<PROJ-NNNNN or null>",
    "affects_versions": ["<affected versions from Jira>"],
    "previous_analysis_notes": "<any conclusions or analysis captured in Jira description>",
    "priority": "<Jira priority>",
    "status": "<Jira status>"
  },
  "information_sources": [
    {
      "type": "Jira",
      "verified": true,
      "url": "https://redhat.atlassian.net/browse/<PROJ-NNNNN>"
    },
    {
      "type": "NVD",
      "verified": true,
      "url": "https://nvd.nist.gov/vuln/detail/CVE-YYYY-NNNNN"
    },
    {
      "type": "GitHub Security Advisory",
      "verified": true,
      "url": "https://github.com/advisories/GHSA-xxxx-xxxx-xxxx"
    }
  ],
  "information_completeness": "COMPLETE",
  "data_quality": "HIGH",
  "conflicts": [],
  "gaps": []
}

internal_context and the Jira entry in information_sources are only populated when a jira_context was passed in (Step 1.5); omit them entirely in direct <CVE-ID> mode.

Mark Information Sources:

  • ✓ "Verified from Jira ticket (internal)"
  • ✓ "Verified from NVD"
  • ✓ "Verified from MITRE"
  • ✓ "Verified from Go vulndb"
  • ✓ "Verified from GitHub Security Advisory"
  • ⚠️ "Based on user-provided information"
  • ⚠️ "Inferred from package repository"
  • ⚠️ "Partial information - some fields missing"

Record conflicts when Jira and public sources disagree:

json
"conflicts": [
  {
    "field": "cvss_score",
    "jira_value": "7.5",
    "public_value": "6.5",
    "resolution": "Used higher value (7.5) for conservative risk assessment"
  }
]

Assess Information Completeness:

  • COMPLETE: All critical fields populated from authoritative sources
  • MOSTLY_COMPLETE: Core info available, some details missing
  • PARTIAL: Only basic info (CVE ID, description, rough severity)
  • MINIMAL: User-provided or very limited data

Identify Gaps:

json
"gaps": [
  "CVSS score not available",
  "Fixed version not confirmed",
  "Vulnerable functions not identified"
]
Step 8: Determine Go Relevance

Assess if CVE is Go-related:

Strong Indicators (HIGH confidence):

  • Found in Go vulnerability database
  • GHSA entry mentions Go/Golang
  • Affected package is a Go module
  • NVD lists Go as affected product

Weak Indicators (MEDIUM confidence):

  • Generic web framework CVE that might affect Go
  • Library with Go bindings
  • Transitive dependency through C libraries

Not Go-related (Exit early):

  • CVE explicitly for other languages (Python, Node.js, etc.)
  • OS/kernel vulnerabilities (unless Go runtime affected)
  • Hardware vulnerabilities

Decision Point:

  • IF clearly NOT Go-related → Return "NOT_APPLICABLE" verdict
  • IF Go-related → Continue analysis
  • IF unclear → Note uncertainty, continue with caution

Return Value

Return structured data to parent command:

json
{
  "skill": "cve-intelligence-gathering",
  "status": "success",
  "cve_profile": {
    "cve_id": "CVE-YYYY-NNNNN",
    "severity": "<CRITICAL|HIGH|MEDIUM|LOW>",
    "cvss_score": "<score>",
    "affected_packages": [...],
    "fixed_versions": [...],
    "description": "...",
    "references": [...]
  },
  "information_quality": {
    "completeness": "<COMPLETE|MOSTLY_COMPLETE|PARTIAL|MINIMAL>",
    "sources": ["<source1>", "<source2>", ...],
    "user_provided": "<true|false>",
    "gaps": []
  },
  "go_relevance": {
    "is_go_related": "<true|false>",
    "confidence": "<HIGH|MEDIUM|LOW>",
    "reasoning": "<explanation>"
  }
}

Error Handling

Invalid CVE Format
text
Error: Invalid CVE identifier format
Expected: CVE-YYYY-NNNNN
Received: {user-input}

Action: Return error, do not proceed

Network/Search Failures
  • Try multiple search strategies
  • Fall back to alternative sources
  • Request user input as last resort
  • Document what was attempted
CVE Not Found Anywhere
text
Warning: CVE-{ID} not found in any database
Possible reasons:
- CVE is very new (not yet published)
- CVE ID is incorrect
- CVE was disputed/rejected
- Private disclosure not yet public

Action: Request user input or exit

Non-Go CVE
text
Info: CVE-{ID} does not appear to affect Go
Affected platforms: {list}

Action: Return NOT_APPLICABLE verdict early

Example: Complete Workflow

text
Step 1: Validate
✓ CVE-YYYY-NNNNN - Valid format

Step 2: Primary Sources
✓ NVD: Found - CVSS <score>, Severity: <severity>
✓ MITRE: Found - CWE-<number>, References available

Step 3: Go-Specific Sources
✓ Go vulndb: Found - <package-name>
✓ GHSA: Found - GHSA-xxxx-xxxx-xxxx
  - Affected: <package-name> <version-range>
  - Fixed: <fixed-version>
  - Vulnerable functions: <function1>, <function2>

Step 4: Remediation Intelligence
✓ GitHub Advisory: Update to <fixed-version>
✓ Release notes: <release-notes-url>
✓ Fix commit: <commit-url>

Step 5: Not needed - sufficient data

Step 6: Not needed - sufficient data

Step 7: Compile Profile
✓ All fields populated
✓ Information completeness: COMPLETE
✓ Data quality: HIGH
✓ No gaps identified

Step 8: Go Relevance
✓ Is Go-related: YES
✓ Confidence: HIGH
✓ Package: <package-name>

Result: Complete vulnerability profile ready for Phase 2 analysis

Integration with analyze-cve

This skill is called from Phase 1 of the analyze-cve skill.

Input from parent:

  • CVE identifier (from the <CVE-ID> argument, or extracted by jira-cve-extraction when --jira=/--jql= was used)
  • jira_context object from the jira-cve-extraction skill (optional — only present when --jira= or --jql= was provided)
  • AUTO_APPROVE (yes/no, default no) — governs the Step 6 fallback-prompt gating

Output to parent:

  • cve_profile — merged vulnerability profile (Jira internal context + public sources when Jira mode was used; public sources only otherwise)
  • information_quality — completeness assessment (noting which fields came from which source)
  • conflict_log — where Jira and public sources disagreed (empty when no Jira context)
  • go_relevance — Go applicability determination
  • Decision on whether to proceed to Phase 2

Decision Flow:

text
IF status = "error" → Exit command
IF go_relevance.is_go_related = false → Generate "Not Applicable" report, exit
IF information_quality.completeness = "MINIMAL" AND user_declined → Exit command
OTHERWISE → Proceed to Phase 2 with profile

© openshift-eng, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/compliance/skills/cve-intelligence-gathering of openshift-eng/ai-helpers.

Open the folder on GitHubat commit a627176

Compare with similar skills

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Cve Remediationrundeck/rundeck6.3k—~2.9kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Cve Intelligence Gathering

What does Cve Intelligence Gathering do?

Gather comprehensive vulnerability information from multiple authoritative sources with fallback strategies. Cve Intelligence Gathering is an agent skill from openshift-eng/ai-helpers.

When should I use Cve Intelligence Gathering?

Cve Intelligence Gathering fits situations like: tasks that involve Vulnerability scanning.

How do I install Cve Intelligence Gathering in Claude Code?

Run `npx skills add openshift-eng/ai-helpers --skill cve-intelligence-gathering -a claude-code`. Or copy the skill folder (plugins/compliance/skills/cve-intelligence-gathering in openshift-eng/ai-helpers) into .claude/skills/cve-intelligence-gathering in your project. Claude Code loads it when a task matches its description.

How do I install Cve Intelligence Gathering in Codex?

Run `npx skills add openshift-eng/ai-helpers --skill cve-intelligence-gathering -a codex`. Or copy the skill folder (plugins/compliance/skills/cve-intelligence-gathering in openshift-eng/ai-helpers) into .agents/skills/cve-intelligence-gathering in your project. Codex loads it when a task matches its description.

Can I use Cve Intelligence Gathering in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add openshift-eng/ai-helpers --skill cve-intelligence-gathering -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cve-intelligence-gathering, .gemini/skills/cve-intelligence-gathering, .github/skills/cve-intelligence-gathering and .opencode/skills/cve-intelligence-gathering in your project.

What does Cve Intelligence Gathering need to run?

SKILL.md names no scripts, command-line tools or credentials: Cve Intelligence Gathering is instructions for the agent only.

Does Cve Intelligence Gathering access the network?

SKILL.md names 3 domains. In commands or code: redhat.atlassian.net, nvd.nist.gov and github.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Cve Intelligence Gathering safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Cve Intelligence Gathering use?

Cve Intelligence Gathering is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cve Intelligence Gathering use?

About 4.1k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Cve Intelligence Gathering?

Skills that share tags, products or a category with Cve Intelligence Gathering: Security Assessment (amd/gaia, 1.6k stars), Building Vulnerability Dashboard With Defectdojo (mukul975/Anthropic-Cybersecurity-Skills, 34k stars), Deepsec Documentation Guide (vercel-labs/deepsec, 8.1k stars) and Shiro Attack CLI (SummerSec/ShiroAttack2, 2.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cve Intelligence Gathering?

openshift-eng (a GitHub organization) maintains it in openshift-eng/ai-helpers, which has 120 GitHub stars. The repository holds 118 skills in this directory. The repository was last updated on October 6, 2026.

Source: openshift-eng/ai-helpers on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.