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 status-analysisgit 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/status-analysis)<a href="https://agentmods.dev/skills/openshift-eng/ai-helpers/status-analysis"><img src="https://agentmods.dev/badge/skills/openshift-eng/ai-helpers/status-analysis/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/status-analysis"><img src="https://agentmods.dev/badge/skills/openshift-eng/ai-helpers/status-analysis.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 | $0.00014 | $0.04269 |
| Opus 5.5 | $0.00006 | $0.01708 |
| Sonnet 5.5 | $0.00003 | $0.00854 |
| Haiku 4.5 | $0.00001 | $0.00427 |
Grade A, and why
status-analysis 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 468 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jira Status Analysis Engine
This skill provides the core analysis logic shared by status-related commands (/jira:status-rollup, /jira:update-weekly-status, and /jira:generate-feature-updates). It handles data collection, activity analysis, and status generation in a unified way.
IMPORTANT FOR AI: This is a procedural skill - when invoked by a command, you should execute the implementation steps defined in this document and its sub-modules. The calling command determines the configuration parameters.
When to Use This Skill
This skill is invoked automatically by:
/jira:status-rollup- Single root issue, outputs as Jira comment/jira:update-weekly-status- Multiple root issues (batch), outputs to Status Summary field/jira:generate-feature-updates- Multiple root issues (batch), outputs as markdown to stdout
Do NOT invoke this skill directly. Use the commands above.
Architecture Overview
For update-weekly-status (Pre-Gathered Data)
┌─────────────────────────────────────────────────────────────────┐
│ /jira:update-weekly-status │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ Python Data Gatherer │
│ (gather_status_data.py) │
│ │
│ • Async HTTP requests (aiohttp) │
│ • Jira: issues, descendants, changelogs │
│ • GitHub: PRs via GraphQL (batched) │
│ • Output: .work/weekly-status/{date}/issues/*.json │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ Status Analysis Engine │
│ ┌───────────────┐ ┌──────────────────┐ ┌──────────────────┐ │
│ │ Read JSON │ │ Activity │ │ PR Activity │ │
│ │ (pre-gathered)│─▶│ Analysis │─▶│ (pre-gathered) │ │
│ └───────────────┘ └──────────────────┘ └──────────────────┘ │
│ │ │
│ ▼ │
│ ┌──────────────────┐ │
│ │ Formatting │ │
│ │ (formatting.md) │ │
│ └──────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ Status Summary field (R/Y/G template) │
└─────────────────────────────────────────────────────────────────┘
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- activity-analysis.md 12 KB
- data-collection.md 15 KB
- external-links.md 12 KB
- formatting.md 23 KB
- scripts/adf.py 1.1 KB runs code
- scripts/gather_status_data.py 59 KB runs code
- scripts/summarize_issue.py 12 KB runs code
- scripts/test_adf.py 945 B runs code
- scripts/triage_issues.py 5.5 KB runs code
- scripts/validate_feature_updates.py 7.2 KB runs code
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.
- 2d ago Changed · +2 lines d8d3d263d142
- 1mo ago First seen · 466 lines · 14 tokens per session scan A 5c045b01166b
status-analysis is a skill published in the GitHub repository openshift-eng/ai-helpers (121 stars, last pushed today), licensed Apache-2.0. It adds 14 tokens to every session and 4,269 once invoked, about $0.0001 per session on Opus 5.5. 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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