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 fetch-job-run-summarygit 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/fetch-job-run-summary)<a href="https://agentmods.dev/skills/wangke19/gemini-ai-helpers/fetch-job-run-summary"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/fetch-job-run-summary/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/fetch-job-run-summary"><img src="https://agentmods.dev/badge/skills/wangke19/gemini-ai-helpers/fetch-job-run-summary.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 | $0.00025 | $0.01327 |
| Opus 5 | $0.00013 | $0.00664 |
| Sonnet 5 | $0.00005 | $0.00265 |
| Haiku 4.5 | $0.00003 | $0.00133 |
Grade A, and why
Fetch Job Run Summary 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 11d 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.
This is a copy
97% identical to fetch-job-run-summary — 12 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fetch Job Run Summary
This skill fetches a summary of a Prow job run from the Sippy API, listing all tests that failed (excluding flakes) along with their error messages.
When to Use This Skill
Use this skill when you need to:
- List all tests that failed in a specific Prow job run
- Understand which components are affected by failures in a job
- Identify dominant error patterns across multiple test failures
- Investigate mass test failure regressions by examining the underlying test failures
- Get a quick overview of a job run's health (pass rate, infrastructure failure, etc.)
Prerequisites
- Python 3: Version 3.6 or later
- Network Access: Must be able to reach
https://sippy.dptools.openshift.org
Implementation
script_path="extensions/ci/skills/fetch-job-run-summary/fetch_job_run_summary.py"
# Text output (AI-readable)
python3 "$script_path" <prow_job_run_id>
# JSON output (structured)
python3 "$script_path" <prow_job_run_id> --format json
Parameters
| Parameter | Required | Description |
|---|---|---|
prow_job_run_id |
Yes | The Prow job run ID (numeric, e.g., 2030845545290928128) |
--format |
No | Output format: text (default) or json |
Extracting a Job Run ID
The job run ID can be extracted from a Prow job URL:
https://prow.ci.openshift.org/view/gs/test-platform-results/logs/<job-name>/<job_run_id>
The last path segment is the job run ID.
API Details
Endpoint: https://sippy.dptools.openshift.org/api/job/run/summary
Query Parameter: prow_job_run_id (required)
Response Fields:
| Field | Type | Description |
|---|---|---|
id |
int | Prow job run ID |
name |
string | Full job name |
release |
string | OpenShift release (e.g., 4.22) |
cluster |
string | Build cluster (e.g., build01) |
url |
string | Prow job URL |
startTime |
string | ISO 8601 start time |
durationSeconds |
int | Job duration in seconds |
overallResult |
string | S (success) or F (failure) |
reason |
string | Human-readable result reason |
infrastructureFailure |
bool | Whether this was an infrastructure failure |
testCount |
int | Total number of tests run |
testFailureCount |
int | Number of failed tests |
testFailures |
dict | Map of test name to error message (excludes flakes) |
variants |
list | Job variant tags |
What ships with it
1 file 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.
- 11d ago First seen · 146 lines · 25 tokens per session scan A c9715c9484db
Fetch Job Run Summary is a skill published in the GitHub repository wangke19/gemini-ai-helpers (2 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 25 tokens to every session and 1,327 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to fetch-job-run-summary, differing in 12 lines, and is treated as a copy.
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