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
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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.