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 openshift-eng/ai-helpers --skill jira-doc-generatorgit clone --depth 1 https://github.com/openshift-eng/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/openshift-eng/ai-helpers/jira-doc-generator)<a href="https://agentmods.dev/skills/openshift-eng/ai-helpers/jira-doc-generator"><img src="https://agentmods.dev/badge/skills/openshift-eng/ai-helpers/jira-doc-generator/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/openshift-eng/ai-helpers/jira-doc-generator"><img src="https://agentmods.dev/badge/skills/openshift-eng/ai-helpers/jira-doc-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00016 | $0.02233 |
| Opus 5 | $0.00008 | $0.01117 |
| Sonnet 5 | $0.00003 | $0.00447 |
| Haiku 4.5 | $0.00002 | $0.00223 |
Grade A, and why
jira-doc-generator scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- Jira Feature Documentation Generator — 86% identical, 14 lines differ
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jira Feature Documentation Generator
This skill provides detailed step-by-step implementation guidance for the /jira:generate-feature-doc command, which generates comprehensive feature documentation by recursively analyzing a Jira feature and all its related issues and GitHub pull requests.
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. Follow the step-by-step instructions below, starting with Step 1.
When to Use This Skill
This skill is automatically invoked by the /jira:generate-feature-doc command and should not be called directly by users.
Prerequisites
- MCP Jira server configured and running (required - see
plugins/jira/README.mdfor setup) - GitHub CLI (
gh) installed and authenticated (for analyzing PRs) - User has read access to Jira issues (including private issues via MCP authentication)
- User has read access to linked GitHub repositories
- Working directory has
.work/jira/feature-doc/for output (will be created if needed)
Implementation Steps
Step 1: Initialize and Fetch Main Feature Issue
Objective: Set up environment and fetch main feature issue.
Actions:
-
Save initial directory:
INITIAL_DIR=$(pwd)(save at start, before any cd commands) -
Check prerequisites: Verify
jqandghCLI are installed and authenticated- If missing, display error with installation instructions
-
Create output directory:
WORK_DIR=$INITIAL_DIR/.work/jira/feature-doc/<feature-key>(usemkdir -p) -
Fetch main feature via
getJiraIssuewith the feature key. If MCP is unavailable, display error pointing toplugins/jira/README.md. -
Parse response: Extract
key,summary,description,issuetype,status- If fetch fails, display error and exit
-
Display progress: Show feature summary and type
Step 2: Analyze Each GitHub PR
Important: This step expects PR data as input from the jira:extract-prs skill (invoked by the command file). The input is structured JSON containing all discovered PRs with their metadata.
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 · 229 lines · 16 tokens per session scan A b8fcc9403168
jira-doc-generator is a skill published in the GitHub repository openshift-eng/ai-helpers (116 stars, last pushed today), licensed Apache-2.0. It adds 16 tokens to every session and 2,233 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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