Load test Figma API integrations and plan for scale. An agent skill from jeremylongshore/tons-of-skills-marketplace.

MITAuto-check passedBackend & APIs

Install Figma Load Scale

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

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace figma-load-scale --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-load-scale .claude/skills/figma-load-scale && 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-load-scale
GitHub stars
2.8k
Token cost
~1.8k tokens
SKILL.md length
237 words
Files
7 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Load test Figma API integrations and plan for scale. An agent skill from jeremylongshore/tons-of-skills-marketplace.

  • Works in 5 steps: k6 Load Test Script → Run Load Tests → Capacity Planning → …
  • Benchmarking API throughput
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 4 more sections
  • Calls brew and apt; reaches api.figma.com; needs FIGMA_FILE_KEY and FILE_KEY

What it does

Figma Load Scale is an agent skill from jeremylongshore/tons-of-skills-marketplace. Load test Figma API integrations and plan for scale. Use when benchmarking API throughput, testing rate limit behavior, or planning capacity for high-volume Figma integrations. Trigger with phrases like "figma load test", "figma scale", "figma benchmark", "figma capacity", "figma throughput".

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/benchmark-report-template.md`, `references/capacity-planning.md` and `references/errors.md`). Compatibility notes: Designed for Claude Code

It sits in Backend & APIs, covering Load testing, Rate limiting and Third-party API integration. It works with Figma. 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

  • Benchmarking API throughput
  • Testing rate limit behavior
  • Planning capacity for high-volume Figma integrations
  • With phrases like figma load test

Example prompts

  • “figma load test”
  • “figma scale”
  • “figma benchmark”
  • “/figma-load-scale”

Requirements

  • A credential in FILE_KEY
  • A credential in FIGMA_FILE_KEY
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(k6:*), Bash(node:*)

Workflow steps

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

  1. k6 Load Test Script
  2. Run Load Tests
  3. Capacity Planning
  4. Scaling Strategies
  5. Benchmark Report Template

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
    • Bash(k6:*)
    • Bash(node:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • brew
    • apt

    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:

    • grafana.com
    • developers.figma.com
    • github.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • FIGMA_FILE_KEY
    • FILE_KEY

    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 Load Scale loads about 1.8k tokens when it runs, and up to ~3.6k if it reads all its reference files. Until then it costs about 78 tokens; SKILL.md has 237 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~78
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.6k

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). 237 words, ~1,844 tokens.

Download SKILL.mdSave it as .claude/skills/figma-load-scale/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
figma-load-scale
description
Load test Figma API integrations and plan for scale. Use when benchmarking API throughput, testing rate limit behavior, or planning capacity for high-volume Figma integrations. Trigger with phrases like "figma load test", "figma scale", "figma benchmark", "figma capacity", "figma throughput".
allowed-tools
Read, Write, Edit, Bash(k6:*), Bash(node:*)
compatibility
Designed for Claude Code
version
1.6.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, figma

Figma Load & Scale

Overview

Test and plan for the throughput limits of your Figma API integration. Figma's rate limits use a leaky bucket algorithm -- this skill helps you find the bucket size for your plan tier and design your integration to stay within it.

Prerequisites

  • k6 load testing tool (brew install k6 or apt install k6)
  • Figma test PAT (do not load test with production token)
  • A test Figma file (not your production design system)

Instructions

Step 1: k6 Load Test Script
javascript
// figma-load-test.js
import http from 'k6/http';
import { check, sleep } from 'k6';
import { Rate, Trend } from 'k6/metrics';

const figmaErrors = new Rate('figma_errors');
const figmaLatency = new Trend('figma_latency', true);

export const options = {
  scenarios: {
    // Test 1: Find your rate limit ceiling
    rate_limit_probe: {
      executor: 'constant-arrival-rate',
      rate: 10,           // 10 requests per second
      timeUnit: '1s',
      duration: '2m',
      preAllocatedVUs: 5,
      maxVUs: 20,
    },
  },
  thresholds: {
    figma_errors: ['rate<0.10'],        // Less than 10% errors
    figma_latency: ['p(95)<3000'],      // P95 under 3 seconds
    http_req_duration: ['p(99)<5000'],  // P99 under 5 seconds
  },
};

const PAT = __ENV.FIGMA_PAT;
const FILE_KEY = __ENV.FIGMA_FILE_KEY;

export default function () {
  // Use a lightweight endpoint for rate limit testing
  const res = http.get(
    `https://api.figma.com/v1/files/${FILE_KEY}?depth=1`,
    {
      headers: { 'X-Figma-Token': PAT },
      tags: { endpoint: 'files' },
    }
  );

  figmaLatency.add(res.timings.duration);

  const isError = res.status !== 200;
  figmaErrors.add(isError);

  check(res, {
    'status is 200': (r) => r.status === 200,
    'not rate limited': (r) => r.status !== 429,
    'latency < 2s': (r) => r.timings.duration < 2000,
  });

  if (res.status === 429) {
    const retryAfter = parseInt(res.headers['Retry-After'] || '60');
    console.log(`Rate limited. Retry-After: ${retryAfter}s`);
    sleep(retryAfter);
  } else {
    sleep(0.1); // 100ms between requests
  }
}
Step 2: Run Load Tests
bash
# Probe rate limits
k6 run \
  --env FIGMA_PAT="${FIGMA_PAT}" \
  --env FIGMA_FILE_KEY="${FIGMA_FILE_KEY}" \
  figma-load-test.js

# Export results to JSON for analysis
k6 run \
  --env FIGMA_PAT="${FIGMA_PAT}" \
  --env FIGMA_FILE_KEY="${FIGMA_FILE_KEY}" \
  --out json=results.json \
  figma-load-test.js
Step 3: Capacity Planning
typescript
interface FigmaCapacityPlan {
  planTier: string;
  measuredLimitPerMinute: number;
  currentUsagePerMinute: number;
  headroomPercent: number;
  recommendation: string;
}

function planCapacity(
  measuredLimit: number,
  currentUsage: number,
  planTier: string
): FigmaCapacityPlan {
  const headroom = ((measuredLimit - currentUsage) / measuredLimit) * 100;

  let recommendation: string;
  if (headroom > 50) {
    recommendation = 'Adequate capacity. Monitor monthly.';
  } else if (headroom > 20) {
    recommendation = 'Approaching limits. Implement caching and batching.';
  } else {
    recommendation = 'Near capacity. Upgrade plan or reduce request volume.';
  }

  return {
    planTier,
    measuredLimitPerMinute: measuredLimit,
    currentUsagePerMinute: currentUsage,
    headroomPercent: Math.round(headroom),
    recommendation,
  };
}
Step 4: Scaling Strategies
typescript
// Strategy 1: Request coalescing
// Multiple callers requesting the same file get a single API call
class RequestCoalescer {
  private pending = new Map<string, Promise<any>>();

  async get(key: string, fetcher: () => Promise<any>): Promise<any> {
    if (this.pending.has(key)) {
      return this.pending.get(key)!;
    }

    const promise = fetcher().finally(() => this.pending.delete(key));
    this.pending.set(key, promise);
    return promise;
  }
}

const coalescer = new RequestCoalescer();

// 10 simultaneous requests for the same file = 1 API call
const results = await Promise.all(
  Array(10).fill(null).map(() =>
    coalescer.get(fileKey, () => figmaClient.getFile(fileKey))
  )
);

// Strategy 2: Stagger requests across time
import PQueue from 'p-queue';

const figmaQueue = new PQueue({
  concurrency: 3,
  interval: 1000,
  intervalCap: 5, // Max 5 requests per second
});

// Strategy 3: Pre-fetch during off-peak hours
// Run design token sync at 3 AM, cache results for the day
Step 5: Benchmark Report Template
markdown
## Figma API Benchmark Report
**Date:** YYYY-MM-DD
**Plan:** [Starter/Pro/Org/Enterprise]
**Seat:** [Full/Collab/Viewer]

### Rate Limit Findings
| Endpoint | Measured Limit/min | First 429 At | Retry-After |
|----------|-------------------|--------------|-------------|
| GET /v1/files/:key?depth=1 | ~30 | Request #31 | 60s |
| GET /v1/files/:key/nodes | ~30 | Request #32 | 60s |
| GET /v1/images/:key | ~20 | Request #21 | 60s |

### Latency
| Endpoint | P50 | P95 | P99 |
|----------|-----|-----|-----|
| /v1/files (depth=1) | 200ms | 500ms | 1200ms |
| /v1/files (full) | 800ms | 2000ms | 4000ms |
| /v1/images | 300ms | 800ms | 1500ms |

### Recommendations
- Cache file metadata (changes infrequently)
- Use webhooks instead of polling
- Batch node IDs in single requests
- Use `depth=1` unless full tree is needed

Output

  • k6 load test measuring actual rate limits
  • Capacity plan with headroom analysis
  • Scaling strategies implemented
  • Benchmark report documented

Error Handling

IssueCauseSolution
All requests 429'dRate too aggressiveStart lower, ramp gradually
Inconsistent limitsShared rate limit bucketOther services using same token
k6 connection errorsToo many parallel VUsReduce preAllocatedVUs
Results vary between runsLeaky bucket stateWait 5min between test runs

Examples

Run the Step 1 k6 script against a staging file and read the two numbers that matter:

bash
k6 run --vus 5 --duration 2m figma-load-test.js
text
http_req_duration..............: avg=412ms p(95)=890ms
http_req_failed................: 2.1%  (all 429 — rate limit ceiling found)
figma_rate_limited.............: 27    ✗ first 429 at ~55 req/min sustained

That output feeds Step 3 capacity planning directly: at ~55 req/min per token before 429s, a 10,000-file nightly sync needs batching via /nodes?ids= (Step 4) or multiple OAuth users — not more concurrency.

Record results in the benchmark template: references/benchmark-report-template.md.

Resources

Next Steps

For reliability patterns, see figma-reliability-patterns.

© 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 6 other files (references) in skills/.curated/figma-load-scale of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/benchmark-report-template.md
  • references/capacity-planning.md
  • references/errors.md
  • references/k6-load-test-script.md
  • references/run-load-tests.md
  • references/scaling-strategies.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Figma Load Scale next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Figma Load Scale compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Figma Load Scale this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.8kAutomated safety check: PassMIT
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Venice API Keysveniceai/skills144—~3.8kAutomated safety check: PassMIT
Venice API Overviewveniceai/skills144—~3.5kAutomated safety check: PassMIT
API IntegrationHack23/cia239—~1.9kAutomated safety check: PassApache-2.0
Frappe Core APIImpertio-Studio/Frappe_Claude_Skill_Package189—~3.2kAutomated safety check: PassMIT

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Works with

Questions about Figma Load Scale

What does Figma Load Scale do?

Load test Figma API integrations and plan for scale. An agent skill from jeremylongshore/tons-of-skills-marketplace. Figma Load Scale is an agent skill from jeremylongshore/tons-of-skills-marketplace. Load test Figma API integrations and plan for scale.

When should I use Figma Load Scale?

Figma Load Scale fits situations like: benchmarking API throughput; testing rate limit behavior; planning capacity for high-volume Figma integrations; with phrases like figma load test.

How do I install Figma Load Scale in Claude Code?

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

How do I install Figma Load Scale in Codex?

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

Can I use Figma Load Scale 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-load-scale -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-load-scale, .gemini/skills/figma-load-scale, .github/skills/figma-load-scale and .opencode/skills/figma-load-scale in your project.

What does Figma Load Scale need to run?

Going by SKILL.md and its folder, Figma Load Scale needs the command-line tools its instructions call (brew and apt) and credentials named FIGMA_FILE_KEY and FILE_KEY. Our summary lists: A credential in FILE_KEY; A credential in FIGMA_FILE_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(k6:*), Bash(node:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Figma Load Scale 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: grafana.com, developers.figma.com and github.com. This is read from the text; nothing was executed.

Is Figma Load Scale 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 Load Scale use?

Figma Load Scale 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 Load Scale use?

About 1.8k tokens (SKILL.md is roughly 7.4k 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 1.7k tokens, read only when the agent opens those files.

What are the alternatives to Figma Load Scale?

Skills that share tags, products or a category with Figma Load Scale: Bfl API (black-forest-labs/skills, 128 stars), Venice API Keys (veniceai/skills, 144 stars), Venice API Overview (veniceai/skills, 144 stars) and API Integration (Hack23/cia, 239 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Figma Load Scale?

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.