clade-observability

DevOps & Security

Monitor Claude API calls — log tokens, latency, costs, errors, and Use when working with observability patterns. set up alerts for production Claude integrations. Trigger with "anthropic monitoring", "claude observability", "track claude usage", "anthropic logging".

QUICK START

How to use this skill

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I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/HEAD/plugins/saas-packs/claude-pack/skills/clade-observability/SKILL.md

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Anthropic Observability

Overview

Every messages.create call should be instrumented. Track tokens, latency, cost, model, and errors.

Logging Wrapper

import Anthropic from '@claude-ai/sdk';

const client = new Anthropic();

async function trackedCreate(params: Anthropic.MessageCreateParams) {
  const start = performance.now();
  try {
    const message = await client.messages.create(params);
    const durationMs = Math.round(performance.now() - start);

    const log = {
      timestamp: new Date().toISOString(),
      model: message.model,
      input_tokens: message.usage.input_tokens,
      output_tokens: message.usage.output_tokens,
      cache_read_tokens: message.usage.cache_read_input_tokens || 0,
      duration_ms: durationMs,
      stop_reason: message.stop_reason,
      estimated_cost: estimateCost(message.model, message.usage),
    };
    console.log('anthropic_request', JSON.stringify(log));

    return message;
  } catch (err) {
    const durationMs = Math.round(performance.now() - start);
    console.error('anthropic_error', JSON.stringify({
      timestamp: new Date().toISOString(),
      model: params.model,
      error_type: err instanceof Anthropic.APIError ? err.error?.type : 'unknown',
      status: err instanceof Anthropic.APIError ? err.status : null,
      request_id: err instanceof Anthropic.APIError ? err.headers?.['request-id'] : null,
      duration_ms: durationMs,
    }));
    throw err;
  }
}

function estimateCost(model: string, usage: Anthropic.Usage): number {
  const rates: Record<string, [number, number]> = {
    'claude-opus-4-20250514': [15, 75],
    'claude-sonnet-4-20250514': [3, 15],
    'claude-haiku-4-5-20251001': [0.80, 4],
  };
  const [inputRate, outputRate] = rates[model] || [3, 15];
  return (usage.input_tokens * inputRate + usage.output_tokens * outputRate) / 1_000_000;
}

Key Metrics to Track

Metric	Source	Alert Threshold
Error rate	error logs	> 5% over 5 minutes
p95 latency	duration_ms	> 10s (Sonnet)
Daily cost	estimated_cost sum	> 2x daily average
429 rate	error_type = rate_limit	> 10/minute
529 rate	error_type = overloaded	> 5/minute
Token usage	input_tokens + output_tokens	> daily budget

Anthropic Console Monitoring

Usage dashboard: console.anthropic.com → Usage
Spending limits: console.anthropic.com → Settings → Limits
API logs: Not available via API — use your own logging

Output

Every Claude API call logged with tokens, latency, cost estimate, and model
Error calls logged with request ID, status code, and error type
Metrics dashboarded: error rate, p95 latency, daily cost, 429/529 rates
Spending alerts configured in Anthropic console

Error Handling

Error	Cause	Solution
API Error	Check error type and status code	See `clade-common-errors`

Examples

See Logging Wrapper with trackedCreate(), estimateCost() function, Key Metrics table with alert thresholds, and Anthropic Console Monitoring section above.

Resources

Next Steps

See clade-incident-runbook for when things go wrong.

Prerequisites

Completed clade-install-auth
Logging infrastructure (console, structured logs, or observability platform)
Production Claude integration to monitor

Instructions

Step 1: Review the patterns below

Each section contains production-ready code examples. Copy and adapt them to your use case.

Step 2: Apply to your codebase

Integrate the patterns that match your requirements. Test each change individually.

Step 3: Verify

Run your test suite to confirm the integration works correctly.