Agent Skills: Anthropic Observability

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UncategorizedID: jeremylongshore/claude-code-plugins-plus-skills/clade-observability

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pnpm dlx add-skill https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/HEAD/plugins/saas-packs/claude-pack/skills/clade-observability

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plugins/saas-packs/claude-pack/skills/clade-observability/SKILL.md

Skill Metadata

Name
clade-observability
Description
"Monitor Claude API calls \u2014 log tokens, latency, costs, errors,\

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.