Installable skillMIT

Anima Performance Tuning

Optimize Anima code generation performance with caching, parallelism,

BY jeremylongshoreUPDATED Oct 27, 2026
INTENDED FOR✳Claude CodeInstall in a listed agent.

instructions.md

---
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:*)
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
compatibility: Requires Node.js 20+, approved Anima API access, current Anima SDK documentation, and authorized Figma or website source access
---
# Anima Performance Tuning

## Overview

Improve design-to-code throughput without treating cache hits or smaller output
as success unless the result still matches the approved design version,
accessibility expectations, and project build contract.

## Measurement Contract

Record source-fetch, queue, generation, asset, validation, and review durations
separately. Establish targets from the team's own representative fixtures and
provider agreement; do not present illustrative latency or quota numbers as an
Anima service-level objective.

## Prerequisites

- A representative staging fixture and a baseline measurement of generation
  duration, cache hit rate, failure rate, and generated-code validation result.
- A version-aware cache key and retention policy that ties each artifact to
  Figma source version, node ID, and generation settings.
- Review gates for generated output so performance changes cannot automatically
  replace approved components or strip required licenses/accessibility content.

## Authentication

Load `ANIMA_TOKEN` and the source-scoped `FIGMA_TOKEN` only in the backend worker.
Performance tests use synthetic allowlisted sources; do not broaden credentials
or retry authorization failures to make a benchmark complete.

## Instructions

### Step 1: File-Based Generation Cache

```typescript
// 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 };
```

### Step 2: Incremental Generation (Only Changed Components)

```typescript
// 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;
}
```

### Step 3: Validate Output Without Semantic Rewriting

```typescript
// 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'),
  };
}
```

## Tool Discipline

Use Read and Grep to inspect the existing integration and generated diff before changing anything. Use Write or Edit only inside the approved generated-code, test, or configuration paths. Use the declared Bash commands only for the explicit install, validation, or diagnostic steps in this workflow; never print tokens, source designs, generated source, or private website captures.

## Output

- File-based generation cache with TTL
- Incremental generation (only changed components)
- Output size and digest measurements without destructive rewriting

## Examples

Benchmark ten approved staging components once without cache and once with the
cache keyed by source version, node ID, and settings. Compare duration, API
calls, output size, lint/type results, and visual review rather than just cache
hit rate. Regenerate only components whose recorded source version changed, and
keep the prior generated artifact available for diff review. If a cache entry
cannot prove its source version, post-processing changes required behavior, or
rate limits increase, disable the optimization and return to the prior
validated generation path while investigating the aggregate measurements.

## Error Handling

| Failure | Response |
|---------|----------|
| Cache artifact lacks valid source/version metadata | Refuse reuse and regenerate the approved component. |
| Incremental detector cannot determine change state | Treat the affected component as needing controlled regeneration. |
| Optimizer changes semantics or removes required content | Revert the post-processing rule and restore the reviewed artifact. |
| Throughput increases provider failures or rate limits | Reduce concurrency, apply bounded backoff, and preserve user-visible job state. |

## Resources

- [Anima API](https://docs.animaapp.com/docs/anima-api)
- [Figma API Nodes](https://www.figma.com/developers/api#get-file-nodes-endpoint)
COMPATIBILITY & REFERENCES

Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.