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 vizra-ai/vizra-adk --skill vizra-evaluationgit clone --depth 1 https://github.com/vizra-ai/vizra-adkWrote 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/vizra-ai/vizra-adk/vizra-evaluation)<a href="https://agentmods.dev/skills/vizra-ai/vizra-adk/vizra-evaluation"><img src="https://agentmods.dev/badge/skills/vizra-ai/vizra-adk/vizra-evaluation/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/vizra-ai/vizra-adk/vizra-evaluation"><img src="https://agentmods.dev/badge/skills/vizra-ai/vizra-adk/vizra-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00026 | $0.02644 |
| Opus 5 | $0.00013 | $0.01322 |
| Sonnet 5 | $0.00005 | $0.00529 |
| Haiku 4.5 | $0.00003 | $0.00264 |
Grade A, and why
Vizra ADK Evaluation Framework 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 13d 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 — 484 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vizra ADK Evaluation Framework
The evaluation framework enables automated testing of AI agents at scale, including LLM-as-a-Judge evaluation patterns.
Core Concepts
| Component | Purpose |
|---|---|
| Evaluation | Test suite containing test cases for an agent |
| Test Case | Input/expected output pair for testing |
| Assertion | Validation rule for agent responses |
| Judge | LLM-based evaluation of response quality |
Creating Evaluations
Basic Evaluation
<?php
namespace App\Evaluations;
use Vizra\VizraADK\Evaluations\BaseEvaluation;
class CustomerServiceEvaluation extends BaseEvaluation
{
/**
* The agent being evaluated
*/
protected string $agent = 'customer_service';
/**
* Evaluation description
*/
protected string $description = 'Evaluates customer service agent responses';
/**
* Define test cases
*/
public function testCases(): array
{
return [
[
'name' => 'greeting_response',
'input' => 'Hello, I need help with my order',
'assertions' => [
'contains_greeting',
'offers_assistance',
'professional_tone',
],
],
[
'name' => 'refund_request',
'input' => 'I want a refund for order #12345',
'context' => [
'order_id' => '12345',
'order_status' => 'delivered',
],
'assertions' => [
'acknowledges_request',
'asks_for_reason',
'explains_policy',
],
],
[
'name' => 'complaint_handling',
'input' => 'This is terrible service! I\'ve been waiting for weeks!',
'assertions' => [
'empathetic_response',
'apologizes',
'offers_solution',
'no_defensive_language',
],
],
];
}
}
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.
- 13d ago First seen · 484 lines · 26 tokens per session scan A af3e5aad8795
Vizra ADK Evaluation Framework is a skill published in the GitHub repository vizra-ai/vizra-adk (295 stars, last pushed 19d ago), licensed MIT. It adds 26 tokens to every session and 2,644 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 2026-08-30.
Other skills, from other repositories
test-reporting
Run the Level 2 dummy agent integration test suite and produce a detailed HTML report with per-test input → outcome analysis.
database-verification
Shell-based database connectivity and integrity checks. Verifies that databases are reachable, schemas match expectations, and data integrity constraints hold.
coverage-analysis
Running coverage tools, interpreting coverage reports, identifying high-risk gaps, and prioritizing which uncovered code to test first.
response-validation
Validate API response structure and content. Detects schema drift, unexpected null values, and abnormal response sizes.
pytest-patterns
Pytest best practices including fixtures, parametrize, markers, and assertion patterns for Python test suites.
edge-case-generation
Systematic edge-case identification including boundary values, null inputs, type mismatches, and error path testing.