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docs: fix CLI references and broken links in README/CONTRIBUTING/CLAUDE.md (#7948)

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2
CLAUDE.md
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@ -75,7 +75,7 @@ Skyvern is a browser automation platform that uses LLMs and computer vision to i
- Browser dependencies installed via Playwright
### LLM Configuration
Configure via environment variables or `skyvern init llm`:
Configure via environment variables or the interactive `skyvern init` wizard:
- Supports OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Gemini, Ollama
- Uses `LLM_KEY` to specify which model to use
- `SECONDARY_LLM_KEY` for lightweight agent operations

14
CONTRIBUTING.md
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@ -53,7 +53,7 @@ All types of contributions are encouraged and valued. See the [Table of Contents
## Code of Conduct
This project and everyone participating in it is governed by the
[Skyvern Code of Conduct](https://github.com/Skyvern-AI/skyvern-agentblob/master/CODE_OF_CONDUCT.md).
[Skyvern Code of Conduct](https://github.com/skyvern-ai/skyvern/blob/master/CODE_OF_CONDUCT.md).
By participating, you are expected to uphold this code. Please report unacceptable behavior
to <enforcement@skyvern.com>.
@ -62,11 +62,11 @@ to <enforcement@skyvern.com>.
> If you want to ask a question, we assume that you have read the available [Documentation](www.skyvern.com/docs).
Before you ask a question, it is best to search for existing [Issues](https://github.com/Skyvern-AI/skyvern-agent/issues) that might help you. In case you have found a suitable issue and still need clarification, you can write your question in this issue. It is also advisable to search the internet for answers first.
Before you ask a question, it is best to search for existing [Issues](https://github.com/skyvern-ai/skyvern/issues) that might help you. In case you have found a suitable issue and still need clarification, you can write your question in this issue. It is also advisable to search the internet for answers first.
If you then still feel the need to ask a question and need clarification, we recommend the following:
- Open an [Issue](https://github.com/Skyvern-AI/skyvern-agent/issues/new).
- Open an [Issue](https://github.com/skyvern-ai/skyvern/issues/new).
- Provide as much context as you can about what you're running into.
- Provide project and platform versions (nodejs, npm, etc), depending on what seems relevant.
@ -101,7 +101,7 @@ A good bug report shouldn't leave others needing to chase you up for more inform
- Make sure that you are using the latest version.
- Determine if your bug is really a bug and not an error on your side e.g. using incompatible environment components/versions (Make sure that you have read the [documentation](www.skyvern.com/docs). If you are looking for support, you might want to check [this section](#i-have-a-question)).
- To see if other users have experienced (and potentially already solved) the same issue you are having, check if there is not already a bug report existing for your bug or error in the [bug tracker](https://github.com/Skyvern-AI/skyvern-agentissues?q=label%3Abug).
- To see if other users have experienced (and potentially already solved) the same issue you are having, check if there is not already a bug report existing for your bug or error in the [bug tracker](https://github.com/skyvern-ai/skyvern/issues?q=label%3Abug).
- Also make sure to search the internet (including Stack Overflow) to see if users outside of the GitHub community have discussed the issue.
- Collect information about the bug:
- Stack trace (Traceback)
@ -118,7 +118,7 @@ A good bug report shouldn't leave others needing to chase you up for more inform
We use GitHub issues to track bugs and errors. If you run into an issue with the project:
- Open an [Issue](https://github.com/Skyvern-AI/skyvern-agent/issues/new). (Since we can't be sure at this point whether it is a bug or not, we ask you not to talk about a bug yet and not to label the issue.)
- Open an [Issue](https://github.com/skyvern-ai/skyvern/issues/new). (Since we can't be sure at this point whether it is a bug or not, we ask you not to talk about a bug yet and not to label the issue.)
- Explain the behavior you would expect and the actual behavior.
- Please provide as much context as possible and describe the *reproduction steps* that someone else can follow to recreate the issue on their own. This usually includes your code. For good bug reports you should isolate the problem and create a reduced test case.
- Provide the information you collected in the previous section.
@ -141,13 +141,13 @@ This section guides you through submitting an enhancement suggestion for Skyvern
- Make sure that you are using the latest version.
- Read the [documentation](www.skyvern.com/docs) carefully and find out if the functionality is already covered, maybe by an individual configuration.
- Perform a [search](https://github.com/Skyvern-AI/skyvern-agent/issues) to see if the enhancement has already been suggested. If it has, add a comment to the existing issue instead of opening a new one.
- Perform a [search](https://github.com/skyvern-ai/skyvern/issues) to see if the enhancement has already been suggested. If it has, add a comment to the existing issue instead of opening a new one.
- Find out whether your idea fits with the scope and aims of the project. It's up to you to make a strong case to convince the project's developers of the merits of this feature. Keep in mind that we want features that will be useful to the majority of our users and not just a small subset. If you're just targeting a minority of users, consider writing an add-on/plugin library.
<!-- omit in toc -->
#### How Do I Submit a Good Enhancement Suggestion?
Enhancement suggestions are tracked as [GitHub issues](https://github.com/Skyvern-AI/skyvern-agent/issues).
Enhancement suggestions are tracked as [GitHub issues](https://github.com/skyvern-ai/skyvern/issues).
- Use a **clear and descriptive title** for the issue to identify the suggestion.
- Provide a **step-by-step description of the suggested enhancement** in as many details as possible.

23
README.md
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@ -65,7 +65,7 @@ If you'd like to try it out, navigate to [app.skyvern.com](https://app.skyvern.c
Choose your preferred setup method:
> **Database default**: `skyvern quickstart` and `skyvern run server` default to a SQLite database at `~/.skyvern/data.db` so the pip path works without Postgres or Docker. To use Postgres instead, pass `--postgres` for a local container or `--database-string` for an existing database. Docker Compose always uses the bundled Postgres service.
> **Database default**: `skyvern quickstart` and `skyvern run server` default to a SQLite database at `~/.skyvern/data.db` so the pip path works without Postgres or Docker. To use Postgres instead, pass `--database-string` for an existing database (or omit `--no-postgres` so `quickstart` starts its own Postgres container). Docker Compose always uses the bundled Postgres service.
### Option A: pip install (Recommended for Python-managed local setup)
@ -88,7 +88,7 @@ pip install "skyvern[all]"
skyvern quickstart
```
The pip quickstart uses SQLite by default. For a local Postgres container, run `skyvern quickstart --postgres`.
The pip quickstart uses SQLite by default. To use a local Postgres container instead, run `skyvern quickstart` (Postgres container is started unless you pass `--no-postgres`), or connect to an existing database with `--database-string=postgresql+psycopg://user:pass@host:5432/dbname`.
### Option B: Docker Compose
@ -135,9 +135,8 @@ uv pip install skyvern
**Installation:**
- Python SDK / cloud API: `pip install skyvern`
- Local server + packaged UI: `pip install "skyvern[all]"` then run `skyvern quickstart`
- Local server + packaged UI with Postgres: `pip install "skyvern[all]"` then run `skyvern quickstart --postgres`
- Packaged UI for an existing API: `pip install "skyvern[ui]"` then run
`skyvern run ui --api-url <api-url> --api-key <api-key>`
- Local server + packaged UI with Postgres: `pip install "skyvern[all]"` then run `skyvern quickstart --database-string=postgresql+psycopg://user:pass@host:5432/dbname`
- Packaged UI for an existing API: `pip install "skyvern[ui]"` then set `VITE_API_BASE_URL` (and `VITE_SKYVERN_API_KEY` if your API requires a key) and run `skyvern run ui`
- TypeScript: `npm install @skyvern/client`
### AI-Powered Page Commands
@ -209,12 +208,16 @@ summary = await page.prompt("Summarize what's on this page")
```bash
skyvern run all
```
Navigate to http://localhost:8080 to run tasks through the web interface. If the packaged UI is missing, `skyvern run ui` will offer to install the matching UI package. For non-interactive setup, use `skyvern run ui --install-ui` or `skyvern run all --install-ui`.
Navigate to http://localhost:8080 to run tasks through the web interface. If the packaged UI is missing, `skyvern run ui` will offer to install the matching UI package.
To run only the packaged UI against an existing Skyvern API, install `skyvern[ui]` and pass
`--api-url`; the CLI infers `--wss-url` from the API URL unless you override it. You can also set
`VITE_API_BASE_URL`, `VITE_WSS_BASE_URL`, `VITE_ARTIFACT_API_BASE_URL`, `VITE_SKYVERN_API_KEY`,
and `VITE_BROWSER_STREAMING_MODE` before running `skyvern run ui`.
To run only the packaged UI against an existing Skyvern API, install `skyvern[ui]` and set the
environment variables below before running `skyvern run ui`:
- `VITE_API_BASE_URL` (e.g. `http://localhost:8000/api/v1`) — points the UI at your Skyvern API
- `VITE_SKYVERN_API_KEY` — the API key if your API requires one
- `VITE_WSS_BASE_URL` — WebSocket endpoint (inferred from `VITE_API_BASE_URL` if unset)
- `VITE_ARTIFACT_API_BASE_URL` — base URL for artifact downloads
- `VITE_BROWSER_STREAMING_MODE` — browser viewport streaming mode
**Python SDK:**
```python

4
docs/developers/debugging/faq.mdx
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@ -153,7 +153,7 @@ For local installations, run `skyvern init` to generate a local API key, which w
<Accordion title="How do I change the LLM model?">
**Cloud:** The model is managed by Skyvern. Contact support for custom model requirements.
**Self-hosted:** Run `skyvern init llm` to reconfigure, or set these environment variables:
**Self-hosted:** Run `skyvern init` to reconfigure, or set these environment variables:
- `LLM_KEY`: Primary model (e.g., `OPENAI_GPT5_5`, `ANTHROPIC_CLAUDE4.7_OPUS`)
- `SECONDARY_LLM_KEY`: Optional lightweight model for faster operations
</Accordion>
@ -355,7 +355,7 @@ OPENAI_API_KEY=sk-...
LLM_KEY=OPENAI_GPT5_5
```
Skyvern supports OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Gemini, and Ollama. Run `skyvern init llm` for guided configuration.
Skyvern supports OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Gemini, and Ollama. Run `skyvern init` for guided configuration.
</Accordion>
---