gamma-observability
Adds observability and monitoring to Gamma API integrations.
Install
mkdir -p .claude/skills/gamma-observability && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5418" && unzip -o skill.zip -d .claude/skills/gamma-observability && rm skill.zipInstalls to .claude/skills/gamma-observability
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Implement comprehensive observability for Gamma integrations.Key capabilities
- →Instrument Gamma API client for metrics collection
- →Implement structured logging for Gamma events
- →Create a health check endpoint for Gamma API
- →Expose Prometheus metrics for Gamma usage
- →Define alerting rules for Gamma API performance
How it works
This skill instruments Gamma API calls to collect metrics on requests, errors, latency, and credit consumption. It also provides structured logging, a health check endpoint, and Prometheus metrics for monitoring and alerting.
Inputs & outputs
When to use gamma-observability
- →Setting up API usage dashboards
- →Logging Gamma generation metrics
- →Tracking API error rates
- →Optimizing credit consumption in Gamma API
About this skill
Gamma Observability
Overview
Implement monitoring, logging, and health checks for Gamma API integrations. Since Gamma does not expose rate limit headers or internal metrics, observability is built around your API call patterns, latency, error rates, credit consumption, and generation success rates.
Prerequisites
- Working Gamma integration (see
gamma-sdk-patterns) - Monitoring stack (Prometheus/Grafana, Datadog, or CloudWatch)
- Logging infrastructure
Instructions
Step 1: Instrumented Client
// src/observability/gamma-metrics.ts
interface GammaMetrics {
requests: number;
errors: number;
generations: number;
completions: number;
failures: number;
totalCredits: number;
totalLatencyMs: number;
errorsByStatus: Record<number, number>;
}
const metrics: GammaMetrics = {
requests: 0, errors: 0,
generations: 0, completions: 0, failures: 0,
totalCredits: 0, totalLatencyMs: 0,
errorsByStatus: {},
};
export function createInstrumentedClient(apiKey: string) {
const base = "https://public-api.gamma.app/v1.0";
const headers = { "X-API-KEY": apiKey, "Content-Type": "application/json" };
async function instrumentedRequest(method: string, path: string, body?: unknown) {
metrics.requests++;
const start = Date.now();
try {
const res = await fetch(`${base}${path}`, {
method, headers,
body: body ? JSON.stringify(body) : undefined,
});
metrics.totalLatencyMs += Date.now() - start;
if (!res.ok) {
metrics.errors++;
metrics.errorsByStatus[res.status] = (metrics.errorsByStatus[res.status] || 0) + 1;
throw new Error(`Gamma ${res.status}: ${await res.text()}`);
}
return res.json();
} catch (err) {
if (!metrics.errorsByStatus[0]) metrics.errorsByStatus[0] = 0;
metrics.totalLatencyMs += Date.now() - start;
throw err;
}
}
return {
generate: async (body: any) => {
metrics.generations++;
return instrumentedRequest("POST", "/generations", body);
},
poll: (id: string) => instrumentedRequest("GET", `/generations/${id}`),
listThemes: () => instrumentedRequest("GET", "/themes"),
listFolders: () => instrumentedRequest("GET", "/folders"),
// Record completion metrics
recordCompletion: (creditsUsed: number) => {
metrics.completions++;
metrics.totalCredits += creditsUsed;
},
recordFailure: () => { metrics.failures++; },
};
}
export function getMetrics() {
return {
...metrics,
avgLatencyMs: metrics.requests > 0
? Math.round(metrics.totalLatencyMs / metrics.requests) : 0,
errorRate: metrics.requests > 0
? (metrics.errors / metrics.requests * 100).toFixed(2) + "%" : "0%",
completionRate: metrics.generations > 0
? (metrics.completions / metrics.generations * 100).toFixed(1) + "%" : "N/A",
avgCreditsPerGeneration: metrics.completions > 0
? Math.round(metrics.totalCredits / metrics.completions) : 0,
};
}
Step 2: Structured Logging
// src/observability/logger.ts
function logGammaEvent(event: string, data: Record<string, any>) {
console.log(JSON.stringify({
timestamp: new Date().toISOString(),
service: "gamma",
event,
...data,
// Never log: apiKey, raw content (may contain PII)
}));
}
// Usage
logGammaEvent("generation.started", {
generationId: "gen_abc123",
outputFormat: "presentation",
contentLength: 500,
});
logGammaEvent("generation.completed", {
generationId: "gen_abc123",
creditsUsed: 42,
latencyMs: 15000,
});
logGammaEvent("generation.failed", {
generationId: "gen_abc123",
error: "Generation failed after 180s",
});
Step 3: Health Check Endpoint
// src/api/health.ts
async function checkGammaHealth() {
const start = Date.now();
try {
const res = await fetch("https://public-api.gamma.app/v1.0/themes", {
headers: { "X-API-KEY": process.env.GAMMA_API_KEY! },
});
const latencyMs = Date.now() - start;
if (!res.ok) {
return { status: "unhealthy", latencyMs, error: `HTTP ${res.status}` };
}
if (latencyMs > 5000) {
return { status: "degraded", latencyMs, message: "High latency" };
}
return { status: "healthy", latencyMs };
} catch (err: any) {
return { status: "unhealthy", latencyMs: Date.now() - start, error: err.message };
}
}
app.get("/health/gamma", async (req, res) => {
const health = await checkGammaHealth();
res.status(health.status === "unhealthy" ? 503 : 200).json(health);
});
Step 4: Prometheus Metrics Endpoint
// src/api/metrics.ts
app.get("/metrics/gamma", (req, res) => {
const m = getMetrics();
res.type("text/plain").send(`
# HELP gamma_requests_total Total API requests
# TYPE gamma_requests_total counter
gamma_requests_total ${m.requests}
# HELP gamma_errors_total Total API errors
# TYPE gamma_errors_total counter
gamma_errors_total ${m.errors}
# HELP gamma_generations_total Total generations started
# TYPE gamma_generations_total counter
gamma_generations_total ${m.generations}
# HELP gamma_completions_total Successful generations
# TYPE gamma_completions_total counter
gamma_completions_total ${m.completions}
# HELP gamma_credits_total Total credits consumed
# TYPE gamma_credits_total counter
gamma_credits_total ${m.totalCredits}
# HELP gamma_avg_latency_ms Average request latency
# TYPE gamma_avg_latency_ms gauge
gamma_avg_latency_ms ${m.avgLatencyMs}
`.trim());
});
Step 5: Alerting Rules
# alerting-rules.yml (Prometheus)
groups:
- name: gamma
rules:
- alert: GammaHighErrorRate
expr: rate(gamma_errors_total[5m]) / rate(gamma_requests_total[5m]) > 0.1
for: 5m
annotations:
summary: "Gamma error rate above 10%"
- alert: GammaHealthUnhealthy
expr: up{job="gamma-health"} == 0
for: 2m
annotations:
summary: "Gamma health check failing"
- alert: GammaHighCreditBurn
expr: rate(gamma_credits_total[1h]) > 100
for: 30m
annotations:
summary: "Gamma credit consumption > 100/hour"
- alert: GammaLowCompletionRate
expr: gamma_completions_total / gamma_generations_total < 0.8
for: 15m
annotations:
summary: "Gamma generation completion rate below 80%"
Key Metrics to Monitor
| Metric | Healthy | Warning | Critical |
|---|---|---|---|
| API error rate | < 5% | 5-10% | > 10% |
| Health check latency | < 2s | 2-5s | > 5s |
| Generation completion rate | > 90% | 80-90% | < 80% |
| Credits per hour | Within budget | 75% of budget | Over budget |
| Average generation time | < 30s | 30-60s | > 60s |
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Metrics not appearing | Scrape config wrong | Check Prometheus targets |
| Health check flapping | Network jitter | Add for: 2m to alert rules |
| Credit alerts too noisy | Thresholds too low | Calibrate to your usage pattern |
| Missing generation metrics | Not calling recordCompletion() | Ensure poll results feed metrics |
Resources
Next Steps
Proceed to gamma-incident-runbook for incident response.
Prerequisites
Limitations
- →Gamma does not expose rate limit headers
- →Gamma does not expose internal metrics
How it compares
This skill builds custom observability around Gamma API usage within the application, as Gamma does not expose internal metrics or rate limit headers directly, unlike APIs with built-in monitoring.
Compared to similar skills
gamma-observability side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| gamma-observability (this skill) | 1 | 27d | Review | Intermediate |
| perplexity-observability | 1 | 27d | No flags | Intermediate |
| distributed-tracing | 5 | 2mo | No flags | Intermediate |
| service-mesh-observability | 5 | 2mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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