Agent skill

Elevenlabs Cost Tuning

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Optimize ElevenLabs costs through model selection, character-efficient patterns, caching, and usage monitoring with budget alerts.

MITAuto-check passedMedia & Creative

Install Elevenlabs Cost Tuning

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill elevenlabs-cost-tuning -a claude-code

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace elevenlabs-cost-tuning --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/elevenlabs-cost-tuning .claude/skills/elevenlabs-cost-tuning && 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
elevenlabs-cost-tuning
GitHub stars
2.8k
Token cost
~1.7k tokens
SKILL.md length
595 words
Files
3 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Optimize ElevenLabs costs through model selection, character-efficient patterns, caching, and usage monitoring with budget alerts.

  • Works in 5 steps: Model-based reduction — route each… → Character-efficient text — run copy… → Real-time quota monitoring —… → …
  • Analyzing ElevenLabs billing
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Elevenlabs Cost Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. 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".

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/examples.md` and `references/implementation.md`). Compatibility notes: Designed for Claude Code

It sits in Media & Creative, covering Text to speech and voice. It works with ElevenLabs. 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

  • Analyzing ElevenLabs billing
  • Reducing character usage
  • Hunting down bill shock
  • Implementing quota monitoring for TTS workloads

Example prompts

  • “elevenlabs cost”
  • “elevenlabs billing”
  • “reduce elevenlabs costs”
  • “/elevenlabs-cost-tuning”

Requirements

  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Bash(curl:*), Bash(node:*)

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Model-based reduction — route each request through selectCostEffectiveModel() so
  2. Character-efficient text — run copy through optimizeTextForTTS() to strip
  3. Real-time quota monitoring — getQuotaStatus() returns used/remaining/percent, a
  4. Cost-aware request guard — guardedTTS() refuses a call that exceeds remaining
  5. Usage tracking — trackUsage() + getUsageSummary() roll up credits by model and

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
    • Bash(curl:*)
    • Bash(node:*)

    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

    Links to these hosts (documentation or services it may open):

    • elevenlabs.io

    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

Elevenlabs Cost Tuning loads about 1.7k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 122 tokens; SKILL.md has 595 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~122
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
~3.9k

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

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). 595 words, ~1,699 tokens.

Download SKILL.mdSave it as .claude/skills/elevenlabs-cost-tuning/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
elevenlabs-cost-tuning
description
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".
allowed-tools
Read, Bash(curl:*), Bash(node:*)
compatibility
Designed for Claude Code
version
1.6.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, voice, ai, elevenlabs, cost, billing

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 monitoring — getQuotaStatus() returns used/remaining/percent, a per-day budget until reset, and a projectedOverage flag from the current usage rate.
  4. Cost-aware request guard — guardedTTS() refuses a call that exceeds remaining quota and force-downgrades to Flash above 90% usage, preventing hard overages.
  5. Usage tracking — trackUsage() + 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:

typescript
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
Show full SKILL.md (231 more words)Show less

Output

Applying this skill produces:

  • A cost-aware TTS layer — selectCostEffectiveModel() + guardedTTS() that pick the cheapest acceptable model per content type and refuse/downgrade calls near the quota.
  • A text optimizer — optimizeTextForTTS() returning { optimized, originalLength, savedCharacters }.
  • A live quota picture — getQuotaStatus() returning plan, used, limit, remaining, pctUsed, dailyBudget, and a projectedOverage boolean.
  • A usage roll-up — getUsageSummary() 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):

typescript
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

© 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 2 other files (references) in skills/.curated/elevenlabs-cost-tuning of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/examples.md
  • references/implementation.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Elevenlabs Cost Tuning 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.

Elevenlabs Cost Tuning compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Elevenlabs Cost Tuning this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.7kAutomated safety check: PassMIT
Musictadaspetra/loop2962 repos~827Automated safety check: PassMIT
Sound Effectstadaspetra/loop2962 repos~1.1kAutomated safety check: PassMIT
Elevenlabs Transcribeqdhenry/Claude-Command-Suite1.3k—~1.5kAutomated safety check: NotesNone
Dubbingelevenlabs/skills482—~3.3kAutomated safety check: PassMIT
Sagtrpc-group/trpc-agent-go1.9k15 repos~574Automated safety check: PassApache-2.0

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Works with

Questions about Elevenlabs Cost Tuning

What does Elevenlabs Cost Tuning do?

Optimize ElevenLabs costs through model selection, character-efficient patterns, caching, and usage monitoring with budget alerts. Elevenlabs Cost Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Optimize ElevenLabs costs through model selection, character-efficient patterns, caching, and usage monitoring with budget alerts.

When should I use Elevenlabs Cost Tuning?

Elevenlabs Cost Tuning fits situations like: analyzing ElevenLabs billing; reducing character usage; hunting down bill shock; implementing quota monitoring for TTS workloads.

How do I install Elevenlabs Cost Tuning in Claude Code?

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

How do I install Elevenlabs Cost Tuning in Codex?

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

Can I use Elevenlabs Cost Tuning 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 elevenlabs-cost-tuning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/elevenlabs-cost-tuning, .gemini/skills/elevenlabs-cost-tuning, .github/skills/elevenlabs-cost-tuning and .opencode/skills/elevenlabs-cost-tuning in your project.

What does Elevenlabs Cost Tuning need to run?

SKILL.md names no scripts, command-line tools or credentials: Elevenlabs Cost Tuning is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Bash(curl:*), Bash(node:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Elevenlabs Cost Tuning access the network?

SKILL.md names 1 domain. As links in the text: elevenlabs.io. This is read from the text; nothing was executed.

Is Elevenlabs Cost Tuning 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 Elevenlabs Cost Tuning use?

Elevenlabs Cost Tuning 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 Elevenlabs Cost Tuning use?

About 1.7k tokens (SKILL.md is roughly 6.8k 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 2.2k tokens, read only when the agent opens those files.

What are the alternatives to Elevenlabs Cost Tuning?

Skills that share tags, products or a category with Elevenlabs Cost Tuning: Music (tadaspetra/loop, 296 stars), Sound Effects (tadaspetra/loop, 296 stars), Elevenlabs Transcribe (qdhenry/Claude-Command-Suite, 1.3k stars) and Dubbing (elevenlabs/skills, 482 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Elevenlabs Cost Tuning?

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.