Set up monitoring, metrics, and alerting for Figma API integrations.

MITAuto-check passedDevOps & Cloud

Install Figma Observability

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill figma-observability -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace figma-observability --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/figma-observability .claude/skills/figma-observability && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
figma-observability
GitHub stars
2.8k
Token cost
~2k tokens
SKILL.md length
194 words
Files
6 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Set up monitoring, metrics, and alerting for Figma API integrations.

  • Works in 4 steps: Instrumented Figma Client → Prometheus Metrics → Alert Rules → …
  • Implementing observability for Figma operations
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 4 more sections
  • Calls curl and jq; reaches api.figma.com

What it does

Figma Observability is an agent skill from jeremylongshore/tons-of-skills-marketplace. Set up monitoring, metrics, and alerting for Figma API integrations. Use when implementing observability for Figma operations, tracking API health, or configuring alerts for rate limits and errors. Trigger with phrases like "figma monitoring", "figma metrics", "figma observability", "figma alerts", "figma dashboard".

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/alert-rules.md`, `references/errors.md` and `references/health-check-with-details.md`). Compatibility notes: Designed for Claude Code

It sits in DevOps & Cloud, covering Observability, Monitoring and alerting and Rate limiting. It works with Figma and Prometheus. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Implementing observability for Figma operations
  • Tracking API health
  • Configuring alerts for rate limits and errors
  • With phrases like figma monitoring

Example prompts

  • “figma monitoring”
  • “figma metrics”
  • “figma observability”
  • “/figma-observability”

Requirements

  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Instrumented Figma Client
  2. Prometheus Metrics
  3. Alert Rules
  4. Health Check with Details

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl
    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.figma.com

    Also links to:

    • prometheus.io
    • opentelemetry.io
    • developers.figma.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Figma Observability loads about 2k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 194 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 194 words, ~1,957 tokens.

Download SKILL.mdSave it as .claude/skills/figma-observability/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
figma-observability
description
Set up monitoring, metrics, and alerting for Figma API integrations. Use when implementing observability for Figma operations, tracking API health, or configuring alerts for rate limits and errors. Trigger with phrases like "figma monitoring", "figma metrics", "figma observability", "figma alerts", "figma dashboard".
allowed-tools
Read, Write, Edit
compatibility
Designed for Claude Code
version
1.6.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, figma

Figma Observability

Overview

Monitor Figma REST API health with custom metrics, structured logging, and alerts. Track request latency, error rates, rate limit headroom, and cache hit rates.

Prerequisites

  • Prometheus or compatible metrics backend (or use OpenTelemetry)
  • Structured logging (pino, winston)
  • Alerting system (PagerDuty, Slack, OpsGenie)

Instructions

Step 1: Instrumented Figma Client
typescript
// Wrap every Figma API call with metrics and logging
class InstrumentedFigmaClient {
  private metrics = {
    requests: 0,
    errors: 0,
    rateLimits: 0,
    totalLatencyMs: 0,
  };

  async request<T>(path: string, token: string): Promise<T> {
    const start = performance.now();
    const endpoint = path.replace(/[a-zA-Z0-9]{15,}/, ':key'); // normalize

    try {
      const res = await fetch(`https://api.figma.com${path}`, {
        headers: { 'X-Figma-Token': token },
      });

      const latencyMs = performance.now() - start;
      this.metrics.requests++;
      this.metrics.totalLatencyMs += latencyMs;

      // Log every request with structured data
      console.log(JSON.stringify({
        service: 'figma',
        endpoint,
        status: res.status,
        latencyMs: Math.round(latencyMs),
        rateLimit: {
          remaining: res.headers.get('X-RateLimit-Remaining'),
          type: res.headers.get('X-Figma-Rate-Limit-Type'),
        },
      }));

      if (res.status === 429) {
        this.metrics.rateLimits++;
        const retryAfter = parseInt(res.headers.get('Retry-After') || '60');
        throw new FigmaRateLimitError(retryAfter);
      }

      if (!res.ok) {
        this.metrics.errors++;
        throw new FigmaApiError(res.status, await res.text());
      }

      return res.json();
    } catch (error) {
      if (!(error instanceof FigmaApiError)) {
        this.metrics.errors++;
        console.error(JSON.stringify({
          service: 'figma',
          endpoint,
          error: error instanceof Error ? error.message : 'Unknown',
          latencyMs: Math.round(performance.now() - start),
        }));
      }
      throw error;
    }
  }

  getMetrics() {
    return {
      ...this.metrics,
      avgLatencyMs: this.metrics.requests > 0
        ? Math.round(this.metrics.totalLatencyMs / this.metrics.requests)
        : 0,
      errorRate: this.metrics.requests > 0
        ? (this.metrics.errors / this.metrics.requests * 100).toFixed(1) + '%'
        : '0%',
    };
  }
}
Step 2: Prometheus Metrics
typescript
import { Registry, Counter, Histogram, Gauge } from 'prom-client';

const registry = new Registry();

const figmaRequests = new Counter({
  name: 'figma_api_requests_total',
  help: 'Total Figma API requests',
  labelNames: ['endpoint', 'status'],
  registers: [registry],
});

const figmaLatency = new Histogram({
  name: 'figma_api_request_duration_seconds',
  help: 'Figma API request duration in seconds',
  labelNames: ['endpoint'],
  buckets: [0.1, 0.25, 0.5, 1, 2, 5, 10],
  registers: [registry],
});

const figmaRateLimitRemaining = new Gauge({
  name: 'figma_rate_limit_remaining',
  help: 'Remaining Figma API rate limit',
  registers: [registry],
});

const figmaCacheHits = new Counter({
  name: 'figma_cache_hits_total',
  help: 'Figma cache hits vs misses',
  labelNames: ['result'], // 'hit' or 'miss'
  registers: [registry],
});

// Expose /metrics endpoint
app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});
Step 3: Alert Rules
yaml
# prometheus-alerts.yml
groups:
  - name: figma
    rules:
      - alert: FigmaHighErrorRate
        expr: |
          rate(figma_api_requests_total{status=~"4..|5.."}[5m])
          / rate(figma_api_requests_total[5m]) > 0.05
        for: 5m
        labels: { severity: warning }
        annotations:
          summary: "Figma API error rate > 5% for 5 minutes"

      - alert: FigmaRateLimited
        expr: figma_rate_limit_remaining < 5
        for: 1m
        labels: { severity: warning }
        annotations:
          summary: "Figma rate limit nearly exhausted"

      - alert: FigmaHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(figma_api_request_duration_seconds_bucket[5m])
          ) > 5
        for: 5m
        labels: { severity: warning }
        annotations:
          summary: "Figma API P95 latency > 5 seconds"

      - alert: FigmaAuthFailure
        expr: figma_api_requests_total{status="403"} > 0
        for: 1m
        labels: { severity: critical }
        annotations:
          summary: "Figma auth failures detected (possible expired PAT)"
Step 4: Health Check with Details
typescript
async function figmaHealthCheck(): Promise<{
  status: 'healthy' | 'degraded' | 'unhealthy';
  details: Record<string, any>;
}> {
  const start = Date.now();

  try {
    const res = await fetch('https://api.figma.com/v1/me', {
      headers: { 'X-Figma-Token': process.env.FIGMA_PAT! },
      signal: AbortSignal.timeout(5000),
    });

    const latencyMs = Date.now() - start;
    const remaining = res.headers.get('X-RateLimit-Remaining');

    return {
      status: res.ok ? (latencyMs > 3000 ? 'degraded' : 'healthy') : 'degraded',
      details: {
        authenticated: res.ok,
        latencyMs,
        rateLimitRemaining: remaining ? parseInt(remaining) : null,
        planTier: res.headers.get('X-Figma-Plan-Tier'),
      },
    };
  } catch {
    return {
      status: 'unhealthy',
      details: { authenticated: false, latencyMs: Date.now() - start },
    };
  }
}

Output

  • Instrumented client logging every Figma API call
  • Prometheus metrics for requests, latency, rate limits, cache
  • Alert rules for error rate, rate limits, latency, auth failures
  • Health check endpoint with Figma connectivity details

Error Handling

IssueCauseSolution
High cardinalityToo many label valuesNormalize endpoint paths
Alert stormsThreshold too lowTune for duration and thresholds
Missing rate limit headersNot all endpoints return themHandle null values gracefully
Metrics not scrapingWrong port or pathVerify Prometheus scrape config

Examples

Scrape the instrumented client's metrics (Step 2) and confirm request tracking works:

bash
curl -s localhost:9090/metrics | /usr/bin/grep figma_
text
figma_api_requests_total{endpoint="/v1/files",status="200"} 1042
figma_api_requests_total{endpoint="/v1/files",status="429"} 3
figma_api_request_duration_seconds_bucket{le="0.5"} 981
figma_rate_limit_remaining 118

Fire the health check with dependency detail (Step 4):

bash
curl -s localhost:3000/health | jq '{status, figma: .checks.figma_api}'
# {"status": "ok", "figma": {"reachable": true, "latency_ms": 212}}

Alert thresholds (429 rate, p95 latency) are in references/alert-rules.md.

Resources

Next Steps

For incident response, see figma-incident-runbook.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/.curated/figma-observability of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/alert-rules.md
  • references/errors.md
  • references/health-check-with-details.md
  • references/instrumented-figma-client.md
  • references/prometheus-metrics.md

Open the folder on GitHubat commit cfae287

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Works with

Categories

Questions about Figma Observability

What does Figma Observability do?

Set up monitoring, metrics, and alerting for Figma API integrations. Figma Observability is an agent skill from jeremylongshore/tons-of-skills-marketplace. Set up monitoring, metrics, and alerting for Figma API integrations.

When should I use Figma Observability?

Figma Observability fits situations like: implementing observability for Figma operations; tracking API health; configuring alerts for rate limits and errors; with phrases like figma monitoring.

How do I install Figma Observability in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill figma-observability -a claude-code`. Or copy the skill folder (skills/.curated/figma-observability in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/figma-observability in your project. Claude Code loads it when a task matches its description.

How do I install Figma Observability in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill figma-observability -a codex`. Or copy the skill folder (skills/.curated/figma-observability in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/figma-observability in your project. Codex loads it when a task matches its description.

Can I use Figma Observability in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill figma-observability -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/figma-observability, .gemini/skills/figma-observability, .github/skills/figma-observability and .opencode/skills/figma-observability in your project.

What does Figma Observability need to run?

Going by SKILL.md and its folder, Figma Observability needs the command-line tools its instructions call (curl and jq). Its frontmatter pre-approves these tools: Read, Write, Edit. Compatibility (from SKILL.md): Designed for Claude Code.

Does Figma Observability access the network?

SKILL.md names 4 domains. In commands or code: api.figma.com; the agent is likely to contact it when it follows the instructions. As links in the text: prometheus.io, opentelemetry.io and developers.figma.com. This is read from the text; nothing was executed.

Is Figma Observability safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Figma Observability use?

Figma Observability is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Figma Observability use?

About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.8k tokens, read only when the agent opens those files.

What are the alternatives to Figma Observability?

Skills that share tags, products or a category with Figma Observability: Happy Infra Metrics and Grafana (slopus/happy, 24k stars), WizTelemetry Platform Service (kubesphere/kubesphere, 17k stars), Redis Observability (redis/agent-skills, 166 stars) and Alicloud Acs Agent Sandbox (cinience/alicloud-skills, 397 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Figma Observability?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.