// диагностика AI-агента
function auditAgent(repo) {
  const agent = loadAgent(repo);
  const issues = scanForRisks(agent);

  if (issues.includes("hallucination")) {
    tightenPrompt(agent.promptTemplate);
    addGuardrails(agent, { grounding: true });
  }

  if (agent.loopDetected) {
    breakLoop(agent, { maxSteps: 6 });
  }

  const tokens = estimateTokenUsage(agent.calls);
  if (tokens.cost > budget.monthly) {
    optimizeCalls(agent.calls);
  }

  runTests(repo, { coverage: true });
  return buildReport(issues, tokens);
}

// финальное решение — за инженером
approvedByEngineer ? ship(agent) : reviewAgain(agent);

// чек-лист перед продакшеном
checklist.verify(["tests", "monitoring", "fallback", "docs"]);

// оптимизация промпта
function tightenPrompt(template) {
  const grounded = addContext(template, kb.facts);
  const guarded = addGuardrails(grounded, { strict: true });
  return validate(guarded, examples.golden);
}

// контроль стоимости токенов
function watchBudget(calls, limit) {
  const cost = sumTokens(calls);
  if (cost > limit) {
    return suggestCache(calls);
  }
  return { ok: true, cost };
}

// перед деплоем
deploy.when(tests.pass && review.approved);

// диагностика AI-агента
function auditAgent(repo) {
  const agent = loadAgent(repo);
  const issues = scanForRisks(agent);

  if (issues.includes("hallucination")) {
    tightenPrompt(agent.promptTemplate);
    addGuardrails(agent, { grounding: true });
  }

  if (agent.loopDetected) {
    breakLoop(agent, { maxSteps: 6 });
  }

  const tokens = estimateTokenUsage(agent.calls);
  if (tokens.cost > budget.monthly) {
    optimizeCalls(agent.calls);
  }

  runTests(repo, { coverage: true });
  return buildReport(issues, tokens);
}

// финальное решение — за инженером
approvedByEngineer ? ship(agent) : reviewAgain(agent);

// чек-лист перед продакшеном
checklist.verify(["tests", "monitoring", "fallback", "docs"]);

// диагностика AI-агента
function auditAgent(repo) {
  const agent = loadAgent(repo);
  const issues = scanForRisks(agent);

  if (issues.includes("hallucination")) {
    tightenPrompt(agent.promptTemplate);
    addGuardrails(agent, { grounding: true });
  }

  if (agent.loopDetected) {
    breakLoop(agent, { maxSteps: 6 });
  }

  const tokens = estimateTokenUsage(agent.calls);
  if (tokens.cost > budget.monthly) {
    optimizeCalls(agent.calls);
  }

  runTests(repo, { coverage: true });
  return buildReport(issues, tokens);
}

// финальное решение — за инженером
approvedByEngineer ? ship(agent) : reviewAgain(agent);

// чек-лист перед продакшеном
checklist.verify(["tests", "monitoring", "fallback", "docs"]);

// оптимизация промпта
function tightenPrompt(template) {
  const grounded = addContext(template, kb.facts);
  const guarded = addGuardrails(grounded, { strict: true });
  return validate(guarded, examples.golden);
}

// контроль стоимости токенов
function watchBudget(calls, limit) {
  const cost = sumTokens(calls);
  if (cost > limit) {
    return suggestCache(calls);
  }
  return { ok: true, cost };
}

// перед деплоем
deploy.when(tests.pass && review.approved);

// диагностика AI-агента
function auditAgent(repo) {
  const agent = loadAgent(repo);
  const issues = scanForRisks(agent);

  if (issues.includes("hallucination")) {
    tightenPrompt(agent.promptTemplate);
    addGuardrails(agent, { grounding: true });
  }

  if (agent.loopDetected) {
    breakLoop(agent, { maxSteps: 6 });
  }

  const tokens = estimateTokenUsage(agent.calls);
  if (tokens.cost > budget.monthly) {
    optimizeCalls(agent.calls);
  }

  runTests(repo, { coverage: true });
  return buildReport(issues, tokens);
}

// финальное решение — за инженером
approvedByEngineer ? ship(agent) : reviewAgain(agent);

// чек-лист перед продакшеном
checklist.verify(["tests", "monitoring", "fallback", "docs"]);