skyvern-browser-automation

name: skyvern-browser-automation description: "Skyvern Browser Automation -- CLI Judgment Procedure workflow skill. Use this skill when the user needs AI-powered browser automation \u2014 navigate sites, fill forms, extract structured data, log in with stored credentials, and build reusable workflows and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off." version: "0.0.1" category: cli-automation tags: ["browser-automation", "mcp", "web-scraping", "form-filling", "ai-agents", "workflow-automation", "skyvern-browser-automation", "ai-powered"] complexity: advanced risk: caution tools: ["cursor", "codex-cli", "claude-code", "gemini-cli", "opencode"] source: community author: "mark1ian" date_added: "2026-04-25" date_updated: "2026-04-25"

Skyvern Browser Automation -- CLI Judgment Procedure

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/skyvern-browser-automation from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Skyvern Browser Automation -- CLI Judgment Procedure Skyvern uses AI to navigate and interact with websites. Every command below is a runnable skyvern invocation.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Credentials, Common Patterns, Limitations, Agent Mode.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Use when you need AI-assisted browser automation for navigation, extraction, form filling, login flows, or reusable website workflows.
• Use when deterministic selectors are unavailable and Skyvern's visual/a11y reasoning can identify page controls.
• Use when a one-off browser task should become a repeatable workflow with run history and verification.
• Use when the request clearly matches the imported source intent: AI-powered browser automation — navigate sites, fill forms, extract structured data, log in with stored credentials, and build reusable workflows.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Classification - Signal - CLI Command - Cost - What Happens
2. Quick check (yes/no) - "is the user logged in?" - skyvern browser validate - 1 LLM + screenshots - Lightweight validation (2 steps max), returns boolean. Cheapest AI option.
3. Quick inspection - "what does the page show?" - skyvern browser extract - 1 LLM + screenshots - Dedicated extraction LLM + schema validation + caching.
4. Single action (known target) - "click #submit" - skyvern browser click/type - 0 LLM - Deterministic Playwright. No AI. Fastest.
5. Single action (unknown target) - "click the submit button" - skyvern browser act - 2-3 LLM, no screenshots - No screenshots in reasoning. Economy a11y tree. For visual targets, use hybrid mode (selector + intent).
6. Same-page multi-step - "fill the form and submit" - skyvern browser act or primitive chain - 2-3 LLM or 0 LLM - Use act when labels are clear. Use click/type/select directly when you know selectors.
7. Throwaway autonomous trial - "try this once", "see if this works" - skyvern browser run-task - Higher - One-off autonomous agent for exploration. Do not use for recurring or multi-page production automations.

Imported Workflow Notes

Imported: Step 1: Classify Your Task (ALWAYS do this first)

MCP note: if you are using the Skyvern MCP instead of the CLI, prefer observe + execute for same-page multi-step UI work. The CLI does not expose that pair directly.

Imported: Step 2: Apply These Decision Rules

1. If the prompt includes a selector, id, XPath, or exact field target, use browser primitives -- not act.
2. If you only need a yes/no answer, use validate -- not extract or act.
3. If the work stays on one page and labels are clear, use act or a primitive chain.
4. If the user says try this once, see if this works, or clearly wants a one-off exploratory trial, use run-task.
5. If the task spans multiple pages and is meant to be reusable, scheduled, repeatable, or explicitly set up as automation, use workflow create.
6. Never type passwords. Always use stored credentials with skyvern browser login.

Imported: Step 3: Create a Session

Every browser command needs a session. Create one first:

# Cloud session (default -- works for public URLs)
skyvern browser session create --timeout 30

# Local session (for localhost URLs or self-hosted mode)
skyvern browser session create --local --timeout 30

# Connect to existing browser via CDP
skyvern browser session connect --cdp "ws://localhost:9222"

Session state persists between commands. After session create, subsequent commands auto-attach. Override with --session pbs_.... Close when done: skyvern browser session close.

Imported: Step 4: Execute by Classification

Quick check (yes/no)

skyvern browser validate --prompt "Is the user logged in? Look for a dashboard or avatar."

Returns true/false. Cheapest AI option -- prefer over extract or act for boolean checks.

Quick inspection

skyvern browser extract \
  --prompt "Extract all product names and prices" \
  --schema '{"type":"object","properties":{"items":{"type":"array","items":{"type":"object","properties":{"name":{"type":"string"},"price":{"type":"string"}}}}}}'

Uses screenshots + dedicated extraction LLM. Better than screenshot+read because Skyvern's LLM interprets the page.

Single action (known target)

skyvern browser click --selector "#submit-btn"
skyvern browser type --text "user@co.com" --selector "#email"
skyvern browser select --value "US" --intent "the country dropdown"

Deterministic. No AI. Three targeting modes:

1. Intent: --intent "the Submit button" (AI finds element)
2. Selector: --selector "#submit-btn" (CSS/XPath, deterministic)
3. Hybrid: both (selector narrows, AI confirms)

Single action (unknown target)

skyvern browser act --prompt "Click the Sign In button"
skyvern browser act --prompt "Close the cookie banner, then click Sign In"

Warning: act has NO screenshots in its LLM reasoning. It uses an economy accessibility tree. Fine for well-labeled elements. For visually complex targets, use MCP observe+click or hybrid mode.

Same-page multi-step

skyvern browser act --prompt "Fill the shipping form and click Continue"

Use act when the fields and buttons are clearly labeled and the flow stays on one page. If you need tighter control, break the work into click, type, select, press-key, and wait.

Throwaway autonomous trial

skyvern browser run-task \
  --url "https://example.com" \
  --prompt "Check whether the checkout flow works end to end and extract the confirmation number"

Use run-task to prove feasibility or do one-off exploration. If the task becomes important enough to rerun, debug, or share, convert it to a workflow.

Multi-page or reusable automation — build a workflow with one block per step

skyvern workflow create --definition @checkout-workflow.yaml
skyvern workflow run --id wpid_123 --wait
skyvern workflow status --run-id wr_789

Each navigation block runs with visual reasoning + verification. Split complex flows into multiple blocks (one per page/step). First run uses AI; subsequent runs replay cached scripts.

Repeated/production

skyvern workflow create --definition @workflow.yaml
skyvern workflow run --id wpid_123 --params '{"email":"user@co.com"}'
skyvern workflow status --run-id wr_789

Split into one block per step. Use navigation blocks for actions, extraction for data. First run uses AI; subsequent runs replay a cached script (10-100x faster). Set --run-with agent to force AI mode for debugging.

Imported: Step 5: Verify

Always verify after page-changing actions:

skyvern browser screenshot                          # visual check
skyvern browser validate --prompt "Was the form submitted successfully?"  # boolean assertion
skyvern browser evaluate --expression "document.title"                    # JS state check

Imported: Step 6: Error Recovery

Imported: Workflow Quick Reference

skyvern workflow create --definition @workflow.yaml   # create
skyvern workflow run --id wpid_123 --wait             # run and wait
skyvern workflow status --run-id wr_789               # check status
skyvern workflow list --search "invoice"              # find workflows
skyvern block schema --type navigation                # discover block types
skyvern block validate --block-json @block.json       # validate before creating

Engine: known path = 1.0 (default). Dynamic planning = 2.0. Split into multiple 1.0 blocks when in doubt. Status lifecycle: created -> queued -> running -> completed | failed | canceled | terminated | timed_out

Imported: Credentials

NEVER type passwords through skyvern browser type or act. Always use stored credentials:

skyvern credentials add --name "my-login" --type password --username "user@co.com"
skyvern credential list                          # find the credential ID
skyvern browser login --url "https://login.example.com" --credential-id cred_123

Types: password, credit_card, secret. Also supports bitwarden, 1password, and azure_vault providers.

Examples

Example 1: Ask for the upstream workflow directly

Use @skyvern-browser-automation to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @skyvern-browser-automation against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @skyvern-browser-automation for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @skyvern-browser-automation using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/skyvern-browser-automation, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Deep-Dive References

Imported: Common Patterns

Login flow:

skyvern credential list                          # find credential ID
skyvern browser session create
skyvern browser navigate --url "https://login.example.com"
skyvern browser login --url "https://login.example.com" --credential-id cred_123
skyvern browser validate --prompt "Is the user logged in?"
skyvern browser screenshot

Pagination loop:

skyvern browser extract --prompt "Extract all rows"
skyvern browser validate --prompt "Is there a Next button that is not disabled?"
# If true:
skyvern browser act --prompt "Click the Next page button"
# Repeat extraction. Stop when: no next button, duplicate first row, or max page limit.

Debugging:

skyvern browser screenshot                       # visual state
skyvern browser evaluate --expression "document.title"
skyvern browser evaluate --expression "document.querySelectorAll('table tr').length"

Imported: Limitations

• Do not use Skyvern to bypass site access controls, rate limits, consent gates, or terms that prohibit automation.
• Browser automation can change remote state; confirm user intent before submitting forms, purchasing, deleting, or sending messages.
• Prefer deterministic selectors for stable production flows; AI actions can misread unlabeled or visually ambiguous controls.
• Store credentials only in the supported credential vaults and never type passwords directly through type or act.

Imported: Agent Mode

All commands accept --json for structured output. Set SKYVERN_NON_INTERACTIVE=1 to prevent prompts. Use skyvern capabilities --json for full command discovery. See references/agent-mode.md.