elevenlabs/skills: Agent Skills for the ElevenLabs API Surface
Collections of skills for building with ElevenLabs
At a glance
- What is it?
- This repository packages ten Agent Skills that teach a compatible coding assistant how to call ElevenLabs text-to-speech, speech-to-text, agents, music, dubbing and related endpoints. It is documentation-as-installable-context, not a library, and the eval harness is the part that decides whether it actually fires.
- Who is it for?
- Adopt this if you already drive an Agent Skills-compatible assistant and want ElevenLabs API calls written correctly on the first attempt, particularly for the less obvious endpoints such as voice-changer, voice-isolator and dubbing. Do not adopt it if you need a runtime library, a pinned API version, or anything that works without an assistant in the loop; there is no package to import here.
- Can I use it commercially?
- Yes. MIT is a permissive licence: you can use, modify and sell software built on it, as long as you keep its copyright and licence notices.
- Is it still maintained?
- Yes. The repository last received commits 4 days ago.
- What is it written in?
- Mainly Python, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 15, 2026, and from our analysis. They are not legal advice.
DEEP OPEN-SOURCE ANALYSIS
The problem is that assistants guess at the ElevenLabs API
An assistant asked to "add voice output" will write something plausible. It may pick the wrong JavaScript package, invent a parameter name, or reach for a REST shape that the SDK does not expose. The repository exists to remove that guessing. Each directory under the root is a skill: text-to-speech, speech-to-text, speech-engine, agents, sound-effects, music, voice-changer, voice-isolator, dubbing, and setup-api-key. The README describes them as following the Agent Skills specification, which means they are consumed by any assistant that implements that specification rather than by one vendor's tool. The intended reader is a developer who is already using such an assistant and wants ElevenLabs calls generated against the documented surface. This is not a library for a build pipeline, and nothing in the material suggests a hosted component. The artefact is context.
What the repository actually contains: skill directories plus an eval harness
The layout is flat and legible. Ten skill directories sit at the top level, and a separate evals/ directory holds the test machinery. The README points to a references/ folder inside each skill for installation guidance, including notes on migrating away from deprecated packages. That detail matters more than it looks: SDK migration instructions age quickly, and placing them next to the skill rather than in a central wiki means a stale note is visible in the same diff as the code example it contradicts. The README also carries an explicit warning that the JavaScript package is @elevenlabs/elevenlabs-js and that npm install elevenlabs pulls an outdated v1.x package. A warning of that specificity is the kind of thing that only gets written after someone has been burned by it, and it is the clearest signal in the material that the repository is maintained against real usage rather than generated from an OpenAPI file.
How a skill reaches your assistant: npx skills add and one environment variable
Installation is a single command from the README:
npx skills add elevenlabs/skills
Configuration is one environment variable, shared by every skill:
export ELEVENLABS_API_KEY="your-api-key"
The README says the key can be obtained through the setup-api-key skill or from the ElevenLabs dashboard, and that the CLI reads ELEVENLABS_API_KEY automatically. SDK examples are given for three surfaces: Python via pip install elevenlabs, JavaScript via npm install @elevenlabs/elevenlabs-js, and a CLI installed with npm install -g @elevenlabs/cli or brew install elevenlabs/tap/elevenlabs. The CLI is described as wrapping the REST API. Note the asymmetry: the environment variable is the only configuration key named anywhere in the README, so there is no per-skill config file, no project-level manifest, and no way to scope one skill to one key. If you work across multiple ElevenLabs accounts, that is a constraint you will hit on day one.
The eval harness is the real differentiator
Most skill collections ship without any way to check whether the skill activates. This one ships evals/run_all.py with two distinct modes. Trigger evals test whether a skill fires for the right queries and are described as taking roughly three minutes. Functional evals test whether the skill produces correct output and are described as taking roughly fifteen minutes. Flags include --trigger-only, --functional-only, --skills to name specific skills, and --model to point at a different model, with cursor-agent --list-models given as the way to enumerate options. Results land in evals/results/<timestamp>/ as report.md plus results.json. The harness requires the Cursor Agent CLI on PATH, overridable with CURSOR_AGENT, and Cursor authentication via cursor-agent login or CURSOR_API_KEY. The README states that functional evals run each case in an isolated cursor-agent workspace under the results tree and do not modify skill sources. That isolation claim is the one worth verifying yourself, because it is the difference between a test suite and a test suite that quietly edits the thing it is testing.
Where this is the wrong tool
Two limits are visible from the material alone. First, the eval harness is bound to Cursor. It needs cursor-agent on PATH and either a login or CURSOR_API_KEY. If your team standardises on a different assistant, you can still use the skills, since the README says they follow the Agent Skills specification and work with any compatible assistant, but you cannot run the repository's own evaluations without Cursor. You would be adopting the skills and writing your own trigger tests. Second, there is no versioning story in the material. No releases were retrieved, and installation is npx skills add against a repository rather than a versioned package. There is no documented way to pin the skill text to a commit, which means a change to a skill directory propagates to anyone who reinstalls. For a solo developer experimenting with the music or sound-effects endpoints, that is fine. For a team that needs reproducible generation across a release cycle, it is a gap you have to close yourself, for example by vendoring the skill directories into your own repository at a known commit.
How it differs from the ElevenLabs SDKs and from a general API reference
The Python and JavaScript SDKs are libraries your code imports; this repository is text your assistant reads. The distinction is not cosmetic. An SDK constrains you at compile or import time, so a wrong parameter name fails loudly. Skill text constrains you at generation time, so a wrong parameter name produces code that looks right until it runs. The upside is coverage of endpoints you would otherwise skip: voice-changer, voice-isolator and dubbing are exactly the operations a developer is least likely to know exist and most likely to implement badly by hand. Against a general API reference, the difference is scope. A reference documents every parameter; a skill encodes the sequence of calls and the setup steps for one task, which is why setup-api-key is itself a skill rather than a page. If you want exhaustive parameter documentation, use the API reference. If you want the assistant to stop inventing a dubbing workflow, use this.
Maintenance cost and the MIT licence
The work of maintaining this falls mostly on the maintainers, since the skills track an external API and the references/ folders carry migration notes. Your cost is the reinstall: npx skills add elevenlabs/skills is not a pinned dependency, so the skill text you reviewed is not necessarily the skill text you get next month. Budget for reading the diff when you update, particularly in the JavaScript examples where the README's warning about the outdated v1.x package lives. The repository is MIT licensed, which permits commercial use, modification and redistribution provided the licence and copyright notice are retained. That is a permissive licence and it is compatible with vendoring the skill directories into a private repository, which is the obvious mitigation for the pinning gap. This is a description of what the licence text permits, not legal advice; if you are redistributing modified skills, read the licence file yourself.
Editorial conclusion
Adopt this if you already drive an Agent Skills-compatible assistant and want ElevenLabs API calls written correctly on the first attempt, particularly for the less obvious endpoints such as voice-changer, voice-isolator and dubbing. Do not adopt it if you need a runtime library, a pinned API version, or anything that works without an assistant in the loop; there is no package to import here. Before depending on it, run python3 evals/run_all.py --trigger-only -v against your own query set, because the trigger evals in the repository use the maintainers' phrasing, and a skill that never fires is indistinguishable from a skill that does not exist.
Community notes