Anima Performance Tuning

What it does

When your agent uses it

• Reducing generation latency
• Optimizing batch component generation
• Improving generated code quality for production use
• With: anima performance

Example prompts

• “anima performance”
• “anima slow”
• “anima optimization”
• “/anima-performance-tuning”

Requirements

• Node.js
• A credential in ANIMA_TOKEN
• A credential in FIGMA_TOKEN
• Compatibility (from SKILL.md): Requires Node.js 20+, approved Anima API access, current Anima SDK documentation, and authorized Figma or website source access
• Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*)

Workflow steps

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

1. 1File-Based Generation Cache
2. 2Incremental Generation (Only Changed Components)
3. 3Validate Output Without Semantic Rewriting

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(npm:*)

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).

  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:

  • docs.animaapp.com
  • figma.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_TOKEN
  • ANIMA_TOKEN

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

• Compatibility

  Requires Node.js 20+, approved Anima API access, current Anima SDK documentation, and authorized Figma or website source access

  From compatibility in the SKILL.md frontmatter.

Context cost

Anima Performance Tuning loads about 1.7k tokens when it runs, and up to ~1.9k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 414 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~84

When it runs · the whole SKILL.md, loaded when a task matches

~1.7k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~1.9k

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

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). 414 words, ~1,738 tokens.

name

anima-performance-tuning

description

Optimize Anima code generation performance with caching, parallelism, and output tuning. Use when reducing generation latency, optimizing batch component generation, or improving generated code quality for production use. Trigger with: "anima performance", "anima slow", "anima optimization", "anima caching".

allowed-tools

Read, Write, Edit, Bash(npm:*)

compatibility

Requires Node.js 20+, approved Anima API access, current Anima SDK documentation, and authorized Figma or website source access

version

2.0.0

argument-hint

[generation-workload]

model

inherit

effort

high

license

MIT

author

Jeremy Longshore <jeremy@intentsolutions.io>

tags

saas, design, figma, anima, performance

// src/performance/cache.ts
import crypto from 'crypto';
import fs from 'fs';
import { Anima } from '@animaapp/anima-sdk';

class GenerationCache {
  private dir: string;

  constructor(cacheDir = '.anima-cache') {
    this.dir = cacheDir;
    fs.mkdirSync(cacheDir, { recursive: true });
  }

  private hash(fileKey: string, sourceRevision: string, nodeId: string, settings: object): string {
    return crypto.createHash('sha256').update(`${fileKey}:${sourceRevision}:${nodeId}:${JSON.stringify(settings)}`).digest('hex');
  }

  async getOrGenerate(
    anima: Anima,
    params: Parameters<Anima['generateCode']>[0],
    sourceRevision: string,
    maxAgeMs: number = 3600000, // 1 hour
  ): Promise<Awaited<ReturnType<Anima['generateCode']>>> {
    const key = this.hash(params.fileKey, sourceRevision, params.nodesId[0], params.settings);
    const path = `${this.dir}/${key}.json`;

    if (fs.existsSync(path)) {
      const stat = fs.statSync(path);
      if (Date.now() - stat.mtimeMs < maxAgeMs) {
        return JSON.parse(fs.readFileSync(path, 'utf8'));
      }
    }

    const result = await anima.generateCode(params);
    fs.writeFileSync(path, JSON.stringify(result));
    return result;
  }

  clearOlderThan(maxAgeMs: number): number {
    let cleared = 0;
    for (const file of fs.readdirSync(this.dir)) {
      const path = `${this.dir}/${file}`;
      if (Date.now() - fs.statSync(path).mtimeMs > maxAgeMs) {
        fs.unlinkSync(path);
        cleared++;
      }
    }
    return cleared;
  }
}

export { GenerationCache };

// src/performance/incremental.ts
// Only regenerate components whose Figma nodes changed

async function getNodeLastModified(fileKey: string, nodeId: string): Promise<string> {
  const res = await fetch(
    `https://api.figma.com/v1/files/${fileKey}/nodes?ids=${nodeId}`,
    { headers: { 'X-Figma-Token': process.env.FIGMA_TOKEN! } }
  );
  const data = await res.json();
  return data.lastModified;
}

async function generateOnlyChanged(
  anima: any,
  fileKey: string,
  nodeIds: string[],
  lastModifiedCache: Map<string, string>,
): Promise<string[]> {
  const changed: string[] = [];

  for (const nodeId of nodeIds) {
    const lastMod = await getNodeLastModified(fileKey, nodeId);
    if (lastMod !== lastModifiedCache.get(nodeId)) {
      changed.push(nodeId);
      lastModifiedCache.set(nodeId, lastMod);
    }
  }

  console.log(`${changed.length}/${nodeIds.length} components changed — regenerating`);
  return changed;
}

// Preserve generated semantics; measure before applying reviewed transforms.
function recordOutput(fileName: string, content: string) {
  return {
    fileName,
    bytes: Buffer.byteLength(content),
    digest: crypto.createHash('sha256').update(content).digest('hex'),
  };
}

© 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 1 other file (references) in skills/.curated/anima-performance-tuning of jeremylongshore/tons-of-skills-marketplace.

• SKILL.md
• references/official-docs.md

Open the folder on GitHubat commit cfae287