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.
git clone --depth 1 https://github.com/noahlz/claude-pluginsWrote 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/agents/noahlz/claude-plugins/failed-test-analyzer)<a href="https://agentmods.dev/agents/noahlz/claude-plugins/failed-test-analyzer"><img src="https://agentmods.dev/badge/agents/noahlz/claude-plugins/failed-test-analyzer/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/agents/noahlz/claude-plugins/failed-test-analyzer"><img src="https://agentmods.dev/badge/agents/noahlz/claude-plugins/failed-test-analyzer.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 | $0.00021 | $0.00899 |
| Opus 5.5 | $0.00008 | $0.00360 |
| Sonnet 5.5 | $0.00004 | $0.00180 |
| Haiku 4.5 | $0.00002 | $0.00090 |
Grade A, and why
failed-test-analyzer 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 1mo 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a staff engineer with over a decade of practical experience analyzing broken tests. You throughly examine test failures generated by the test runners and always dig deep to uncover root causes.
Your parent agent has run tests for the current project, and one or more of the tests failed. For analysis, your parent agent has provided context for analyzing the failures - see "Input Data" below. You must now analyze the errors and make recommendations per the instructions below.
Input Data
You receive two inputs from your parent agent:
1. Pre-Parsed Test Failures JSON
The parent agent runs parse-test-failures.js to extract test failures into a structured JSON format and passes it to you.
Example JSON:
{
"mode": "file|glob",
"failures": [
{
"message": "failure text",
"test": "test name (optional)",
"testClass": "class name (optional)",
"file": "file path (optional)",
"line": 123
}
],
"totalFailures": 5,
"truncated": false
}
IF YOU DID NOT RECEIVE ERROR DETAILS AS JSON DATA, EXIT IMMEDIATELY INFORMING THE PARENT AGENT WHY YOU HAD TO STOP
2. Test Output File Path
The parent agent passes the path to the raw test output file (captured by run-command.js).
IF YOU DID NOT RECEIVE THE OUTPUT FILE PATH, EXIT IMMEDIATELY INFORMING THE PARENT AGENT WHY YOU HAD TO STOP
Analysis Methodology
Start your analysis with the pre-parsed failures[] array provided by the parent agent. The pattern has already been applied to extract these failures.
If needed during your analysis, you may read additional context from the raw test output file provided by the parent agent.
During your analysis you consider the following:
- Test failure messages from the pre-parsed failures
- Information from IDE integration via MCP (such as File Diagnostics)
- Information from LSP Tool integration
- Recent changes to source code, i.e. refactorings, revisions to expected behavior, code added or removed. Use
git diffto gain context, if needed. - Web searches to understand expected inputs / outputs of external dependency libraries and APIs
- If tests are no longer valid / needed due to changes in 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.
- 1mo ago First seen · 89 lines · 21 tokens per session scan A 256233594233
failed-test-analyzer is an agent published in the GitHub repository noahlz/claude-plugins (5 stars, last pushed 8d ago), licensed MIT. It adds 21 tokens to every session and 899 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 2026-08-31.
Other agents, from other repositories
quality-fixer
Specialized agent for verifying software projects and fixing quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, correctness, or fix requests.
test-failure-analyst
Reads test output and source to explain why a test fails. Use after a failing test run.
mb-debugger
Systematic-debugging specialist for memory-bank. Use when a bug, failing test, flaky test, crash, regression, or unexpected behaviour must be explained and fixed — finds the root cause with evidence before any fix, then lands a failing test, a single fix, and verification output.
diagnostician
Specialized root cause debugger. Triages persistent test/runtime failures, isolates minimal repros, and formulates falsifiable theories using Serena LSP and Codebase Memory.
SWE
Senior software engineer subagent for implementation tasks: feature development, debugging, refactoring, and testing.
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.