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 hcarrillo001/retrieval-mcp --skill ticket-test-runnergit clone --depth 1 https://github.com/hcarrillo001/retrieval-mcpWrote 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/hcarrillo001/retrieval-mcp/ticket-test-runner)<a href="https://agentmods.dev/skills/hcarrillo001/retrieval-mcp/ticket-test-runner"><img src="https://agentmods.dev/badge/skills/hcarrillo001/retrieval-mcp/ticket-test-runner/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/hcarrillo001/retrieval-mcp/ticket-test-runner"><img src="https://agentmods.dev/badge/skills/hcarrillo001/retrieval-mcp/ticket-test-runner.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 | $0.00139 | $0.01080 |
| Opus 5 | $0.00069 | $0.00540 |
| Sonnet 5 | $0.00028 | $0.00216 |
| Haiku 4.5 | $0.00014 | $0.00108 |
Grade A, and why
ticket-test-runner 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ticket Test Runner
Turn a Jira ticket into a tested, scored, auto-updated ticket. Given one ticket key, this skill reads the ticket, runs the test it describes in a real browser, scores any AI/text output, and posts the verdict back to Jira.
Required connectors
- Jira MCP — Atlassian Rovo MCP (Cloud) or
mcp-atlassian(Server/DC). Needs read and write (comment + transition). - Playwright MCP (Microsoft) — browser automation.
- RetriEval MCP — output scoring. Only needed for tickets with an
evalblock.
Before starting, confirm these are connected. If one is missing, tell the user exactly which to connect and stop — do not fake any step.
Input
A single ticket key, e.g. PROJ-123. The ticket description must contain a
test block (see references/ticket-format.md). If it doesn't, post a comment
listing the required fields and stop — never guess the test.
Workflow
-
Read the ticket. Fetch the issue by key via the Jira MCP. Find the fenced
```testblock in the description and parse:url,steps,expected, and the optionalevalsection. Readreferences/ticket-format.mdfor the exact spec before parsing. -
Run the test with Playwright. Open
url, execute each step in order (type / click / select / wait as written). Capture the observed result — the text the steps point at — plus a screenshot, and a DOM snapshot if a step fails. Mark each step pass/fail againstexpected. If a selector is missing or a step is ambiguous, mark it BLOCKED and ask; do not assume pass. -
Score the output (only if the ticket has an
evalsection). Build one case —input= the query text,actual_output= the captured answer,expected_output/retrieval_contextfrom the ticket — and call RetriEvalevaluate_casewith the listedmetrics(default: faithfulness, answer_relevancy) at the giventhreshold. Passgenerator_model/judge_modelif the ticket names them. Record each score and pass/fail.
What ships with it
2 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 · 96 lines · 139 tokens per session scan A 19f66dafe023
ticket-test-runner is a skill published in the GitHub repository hcarrillo001/retrieval-mcp (0 stars, last pushed 13d ago), licensed Apache-2.0. It adds 139 tokens to every session and 1,080 once invoked, about $0.0007 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 2026-08-31.
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