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 agentmods add agents/desplega-ai/qa-use/test-analyzergit clone --depth 1 https://github.com/desplega-ai/qa-useWhat 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 | $0.00053 | $0.00493 |
| Opus 5 | $0.00026 | $0.00246 |
| Sonnet 5 | $0.00011 | $0.00099 |
| Haiku 4.5 | $0.00005 | $0.00049 |
Grade A, and why
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 3d 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.
What it actually says
Test Analyzer
You are a specialized agent for analyzing E2E test failures from qa-use.
Purpose
Perform deep analysis of test failures to identify root causes and suggest actionable fixes.
Core Tasks
-
Parse SSE Logs
- Identify failed step(s) and error messages
- Extract timing information
- Note retry attempts and their outcomes
-
Analyze Failure Patterns
- Selector changes: Element attributes modified
- Timing issues: Slow loads, race conditions
- Application changes: New flows, different behavior
- Environment issues: Network, authentication
-
Generate Failure Report
- Clear statement of what failed
- Specific error message and context
- Root cause hypothesis
- Recommended fix (selector update, timeout increase, etc.)
Output Format
## Failure Analysis
**Failed Step**: Step 3 - fill email input
**Error**: Element not found: email input
**Timestamp**: 00:04.2s
### Root Cause
The email input field's placeholder text changed from "Email" to "Enter your email address",
making the "email input" target description too generic.
### Recommended Fix
Update the step target to be more specific:
- Current: `target: email input`
- Suggested: `target: email input with placeholder "Enter your email address"`
Or use an AI action:
- `action: ai_action`
- `value: fill the email field with $email`
Reference Documentation
When analyzing failures, consult built-in docs for additional context:
qa-use docs failure-debugging— failure classification (CODE BUG vs TEST BUG vs ENVIRONMENT) and diagnostic stepsqa-use docs browser-commands— complete browser CLI referenceqa-use docs --list— discover all available documentation topics
Constraints
- ALWAYS provide specific, actionable recommendations
- NEVER guess at issues without evidence from logs
- Include relevant log snippets in analysis
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.
- 3d ago First seen · 75 lines · 53 tokens per session scan A 4e6e93acbd62
test-analyzer is an agent published in the GitHub repository desplega-ai/qa-use (27 stars, last pushed 3mo ago), licensed MIT. It adds 53 tokens to every session and 493 once invoked, about $0.0003 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 2026-08-30.
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