Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/wangke19/gemini-ai-helpersnpx agentmods add skills/wangke19/gemini-ai-helpers/analyze-regressionsWrote 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/analyze-regressions)<a href="https://agentmods.dev/skills/wangke19/gemini-ai-helpers/analyze-regressions"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/analyze-regressions/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/analyze-regressions"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/analyze-regressions.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 | $0.05918 |
| Opus 5 | $0.00009 | $0.02959 |
| Sonnet 5 | $0.00004 | $0.01184 |
| Haiku 4.5 | $0.00002 | $0.00592 |
Grade A, and why
Analyze Regressions 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 8d 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 — 793 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze Regressions
This skill provides functionality to analyze and grade component health for OpenShift releases based on regression management metrics. It evaluates how well components are managing their test regressions by analyzing triage coverage, triage timeliness, and resolution speed.
When to Use This Skill
Use this skill when you need to:
- Grade component health for a specific OpenShift release
- Identify components that need help with regression handling
- Track triage and resolution efficiency across releases
- Generate component quality scorecards
- Produce health reports (text or HTML) for stakeholders
Important Note: Grading is subjective and not meant to be a critique of team performance. This is intended to help identify where help is needed and track progress as we try to improve our regression response rates.
Prerequisites
-
Python 3 Installation
- Check if installed:
which python3 - Python 3.6 or later is required
- Comes pre-installed on most systems
- Check if installed:
-
Network Access
- The scripts require network access to reach the component health API and release dates API
- Ensure you can make HTTPS requests
-
Required Scripts
extensions/teams/skills/get-release-dates/get_release_dates.pyextensions/teams/skills/list-regressions/list_regressions.pyextensions/teams/skills/analyze-regressions/generate_html_report.py(for HTML reports)extensions/teams/skills/analyze-regressions/report_template.html(for HTML reports)
Implementation Steps
Step 1: Parse Arguments
Extract the release version and optional component filter from the command arguments:
- Release format: "X.Y" (e.g., "4.17", "4.21")
- Components (optional): List of component names to filter by
Example argument parsing:
/teams:analyze-regressions 4.17
/teams:analyze-regressions 4.21 --components Monitoring etcd
Step 2: Fetch Release Dates
Run the get_release_dates.py script to determine the development window for the release:
What ships with it
3 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.
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.
- 8d ago First seen · 793 lines · 18 tokens per session scan A 8318623ebc2d
Analyze Regressions 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 5,918 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 2026-09-03.
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