Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wangke19/gemini-ai-helpers --skill extract-prsgit clone --depth 1 https://github.com/wangke19/gemini-ai-helpersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wangke19/gemini-ai-helpers/extract-prs)<a href="https://agentmods.dev/skills/wangke19/gemini-ai-helpers/extract-prs"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/extract-prs/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wangke19/gemini-ai-helpers/extract-prs"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/extract-prs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.02232 |
| Opus 5 | $0.00009 | $0.01116 |
| Sonnet 5 | $0.00004 | $0.00446 |
| Haiku 4.5 | $0.00002 | $0.00223 |
Grade A, and why
Jira Pull Request Extractor scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Uses MCP authentication (no separate curl needed) This is a copy
91% identical to extract-prs — 77 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jira Pull Request Extractor
This skill recursively discovers Jira issues and extracts all associated GitHub Pull Request links.
IMPORTANT FOR AI: This is a procedural skill - when invoked, you should directly execute the implementation steps defined in this document. Do NOT look for or execute external scripts (like extract_prs.py). Follow the step-by-step instructions in the "Implementation" section below.
When to Use This Skill
Use this skill when you need to:
- Discover all GitHub PRs associated with a Jira feature and its subtasks
- Extract PR metadata without analyzing PR content
- Build a complete map of PRs for documentation or release notes
Key characteristics:
- ✅ Always recursive: Automatically discovers all descendant issues via
childIssuesOf()JQL - ✅ PR-only: Extracts only Pull Request URLs (ignores Issue and Commit URLs)
- ✅ Dual-source: Extracts from both changelog remote links and text content (description/comments)
- ✅ Structured output: Returns JSON with PR metadata and deduplication across sources
Prerequisites
- MCP Jira server configured and running (required - see
extensions/jira/README.mdfor setup) jqinstalled for JSON parsing- GitHub CLI (
gh) installed and authenticated for fetching PR metadata - User has read permissions for target Jira issues (including private issues via MCP authentication)
- User has read access to linked GitHub repositories
Output Format
Purpose: This skill returns structured JSON that serves as an interface contract for consuming skills and commands.
Delivery Method:
- Primary: Output JSON directly to the response (no file writes, no user prompts)
- Secondary: Only save to
.work/extract-prs/{issue-key}/output.jsonif user explicitly requests to save results
Schema Version: 1.0
Structure
{
"schema_version": "1.0",
"metadata": {
"generated_at": "2025-11-24T10:30:00Z",
"command": "extract_prs",
"input_issue": "OCPSTRAT-1612"
},
"pull_requests": [
{
"url": "https://github.com/openshift/hypershift/pull/6444",
"state": "MERGED",
"title": "Add support for custom OVN subnets",
"isDraft": false,
"sources": ["comment", "description", "remote_link"],
"found_in_issues": ["CNTRLPLANE-1201", "OCPSTRAT-1612"]
}
]
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 205 lines · 18 tokens per session scan A 05f132ba1247
Jira Pull Request Extractor is a skill published in the GitHub repository wangke19/gemini-ai-helpers (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 2,232 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 91% identical to extract-prs, differing in 77 lines, and is treated as a copy.
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