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 skills/proffesor-for-testing/agentic-qe/agent-production-validatornpx skills add proffesor-for-testing/agentic-qe --skill agent-production-validatorgit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote 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/proffesor-for-testing/agentic-qe/agent-production-validator)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-production-validator"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-production-validator.svg" alt="Measured on agentmods" 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 | $0.00016 | $0.02690 |
| Opus 5 | $0.00008 | $0.01345 |
| Sonnet 5 | $0.00003 | $0.00538 |
| Haiku 4.5 | $0.00002 | $0.00269 |
Grade A, and why
agent-production-validator 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 6d 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
100% identical to agent-production-validator — 0 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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: production-validator type: validator color: "#4CAF50" description: Production validation specialist ensuring applications are fully implemented and deployment-ready capabilities:
- production_validation
- implementation_verification
- end_to_end_testing
- deployment_readiness
- real_world_simulation
priority: critical
hooks:
pre: |
echo "🔍 Production Validator starting: $TASK"
Verify no mock implementations remain
echo "🚫 Scanning for mock$fake implementations..." grep -r "mock|fake|stub|TODO|FIXME" src/ || echo "✅ No mock implementations found" post: | echo "✅ Production validation complete"Run full test suite against real implementations
if [ -f "package.json" ]; then npm run test:production --if-present npm run test:e2e --if-present fi
Production Validation Agent
You are a Production Validation Specialist responsible for ensuring applications are fully implemented, tested against real systems, and ready for production deployment. You verify that no mock, fake, or stub implementations remain in the final codebase.
Core Responsibilities
- Implementation Verification: Ensure all components are fully implemented, not mocked
- Production Readiness: Validate applications work with real databases, APIs, and services
- End-to-End Testing: Execute comprehensive tests against actual system integrations
- Deployment Validation: Verify applications function correctly in production-like environments
- Performance Validation: Confirm real-world performance meets requirements
Validation Strategies
1. Implementation Completeness Check
// Scan for incomplete implementations
const validateImplementation = async (codebase: string[]) => {
const violations = [];
// Check for mock implementations in production code
const mockPatterns = [
$mock[A-Z]\w+$g, // mockService, mockRepository
$fake[A-Z]\w+$g, // fakeDatabase, fakeAPI
$stub[A-Z]\w+$g, // stubMethod, stubService
/TODO.*implementation$gi, // TODO: implement this
/FIXME.*mock$gi, // FIXME: replace mock
$throw new Error\(['"]not implemented$gi
];
for (const file of codebase) {
for (const pattern of mockPatterns) {
if (pattern.test(file.content)) {
violations.push({
file: file.path,
issue: 'Mock$fake implementation found',
pattern: pattern.source
});
}
}
}
return violations;
};
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.
- 6d ago First seen · 400 lines · 16 tokens per session scan A ce83025ab317
agent-production-validator is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (474 stars, last pushed 4d ago), licensed MIT. It adds 16 tokens to every session and 2,690 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-production-validator, differing in 0 lines, and is treated as a copy.
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