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Elevenlabs cost tuning

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/saas-packs/elevenlabs-pack/skills/elevenlabs-cost-tuning

425 plugins, 2,810 skills, 200 agents for Claude Code. Open-source marketplace at tonsofskills.com with the ccpi CLI package manager.

Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill elevenlabs-cost-tuning

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What its author says it does

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Optimize ElevenLabs costs through model selection, character-efficient patterns, caching, and usage monitoring with budget alerts. Use when analyzing ElevenLabs billing, reducing character usage, hunting down bill shock, or implementing quota monitoring for TTS workloads. Trigger with "elevenlabs cost", "elevenlabs billing", "reduce elevenlabs costs", "elevenlabs pricing", "elevenlabs expensive", "elevenlabs budget", "elevenlabs characters", "elevenlabs quota".

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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ElevenLabs Cost Tuning

Overview

Optimize ElevenLabs costs through model selection (Flash = 50% savings), character-efficient text processing, audio caching, and real-time quota monitoring. ElevenLabs bills by character for TTS and by audio minute for STT.

Prerequisites

Instructions

Step 1: Understand the Billing Model

TTS billing (by character):

ModelCredits per Character10K Chars CostBest For
eleven_v31.010,000 creditsMaximum quality
eleven_multilingual_v21.010,000 creditsHigh quality + multilingual
eleven_flash_v2_50.55,000 creditsReal-time / budget-conscious
eleven_turbo_v2_50.55,000 creditsFast + affordable

Other feature billing:

FeatureBilling Basis
Speech-to-Text (Scribe)Per audio minute
Sound EffectsPer generation
Audio Isolation1,000 characters per minute of audio
DubbingPer source audio minute

Plan character limits:

PlanMonthlyPriceCost/1K Chars
Free10,000$0$0
Starter30,000$5$0.17
Creator100,000$22$0.22
Pro500,000$99$0.20
Scale2,000,000$330$0.17

Steps 2–6: Apply the cost levers

Work through the levers in order of savings-per-effort. Each ships as a small, drop-in TypeScript helper — the full source for every step is in implementation.md.

  1. Model-based reduction — route each request through selectCostEffectiveModel() so functional audio (greetings, notifications) uses Flash/Turbo at 0.5x while premium, customer-facing output keeps full-quality models. Biggest single win (50%).
  2. Character-efficient text — run copy through optimizeTextForTTS() to strip markdown, HTML, and redundant whitespace/punctuation before billing counts it (5–15%).
  3. Real-time quota monitoringgetQuotaStatus() returns used/remaining/percent, a per-day budget until reset, and a projectedOverage flag from the current usage rate.
  4. Cost-aware request guardguardedTTS() refuses a call that exceeds remaining quota and force-downgrades to Flash above 90% usage, preventing hard overages.
  5. Usage trackingtrackUsage() + getUsageSummary() roll up credits by model and operation and compute a cache-hit rate so you can see where spend actually goes.

Minimal skeleton — the guard is the piece most workloads adopt first:

import { guardedTTS } from "./elevenlabs/cost-aware-tts";

// Notifications auto-route to Flash (0.5x); guard blocks or downgrades near the limit.
const stream = await guardedTTS("Your table is ready.", VOICE_ID, "notification");

Cost Optimization Checklist

StrategySavingsEffort
Flash/Turbo models for non-premium content50%Low
Cache repeated audio (greetings, prompts)80-95% for cachedMedium
Text optimization (remove markdown, whitespace)5-15%Low
Quota monitoring with budget alertsPrevents overagesMedium
Usage-based billing (Creator+ plans)Avoids hard cutoffLow
Batch short texts into single requestsReduces overheadLow

Output

Applying this skill produces:

  • A cost-aware TTS layerselectCostEffectiveModel() + guardedTTS() that pick the cheapest acceptable model per content type and refuse/downgrade calls near the quota.
  • A text optimizeroptimizeTextForTTS() returning { optimized, originalLength, savedCharacters }.
  • A live quota picturegetQuotaStatus() returning plan, used, limit, remaining, pctUsed, dailyBudget, and a projectedOverage boolean.
  • A usage roll-upgetUsageSummary() reporting total credits/characters, spend by model and operation, and cache-hit rate over a trailing window.

Together these turn an unmonitored, single-model TTS integration into one with per-request cost control, overage prevention, and a spend audit trail.

Examples

Quick shape (full, runnable scenarios in examples.md):

import { getQuotaStatus } from "./elevenlabs/quota-monitor";

const q = await getQuotaStatus();
console.log(`${q.plan}: ${q.pctUsed}% used, ${q.remaining.toLocaleString()} chars left`);
if (q.projectedOverage) console.warn("On pace to exceed quota this cycle");
  • Check quota before a batch run — abort early if the batch would exceed remaining chars.
  • Route content to the cheapest acceptable model — Flash for notifications, eleven_v3 for premium.
  • Trim characters before billing counts them — strip markdown/HTML with optimizeTextForTTS().
  • Roll up 30-day spend — see credits by model and cache-hit rate with getUsageSummary().

See examples.md for the complete code of each.

Error Handling

IssueCauseSolution
quota_exceeded (401)Monthly limit hitUpgrade plan or enable usage-based billing
Unexpected high usageNo monitoringImplement getQuotaStatus() guard
Bill shockWrong model in productionAudit model_id in all TTS calls
Cache not helpingUnique contentCache only repeated content (greetings, errors)

Resources

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