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agent-browser

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

88

2.62x
Quality

85%

Does it follow best practices?

Impact

92%

2.62x

Average score across 6 eval scenarios

SecuritybySnyk

Critical

Do not install without reviewing

The canonical home for this skill is agent-browser in vercel-labs/agent-browser

SKILL.md
Quality
Evals
Security

Quality

Content

70%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with excellent executable examples and a clear core workflow, but it is verbose with redundant sections and broken reference links that undercut conciseness and progressive disclosure. Tightening duplicate content and fixing/aligning the reference set would raise the weaker dimensions.

Suggestions

Consolidate duplicated topics: session management appears in three sections and color-scheme in two — merge into a single authoritative section to improve conciseness.

Fix broken progressive disclosure: either create the missing references/commands.md and references/profiling.md or remove them from the Deep-Dive table so navigation is reliable.

Add explicit validation feedback loops (e.g., diff/check after auth and state save/load) to destructive and batch operations to lift workflow clarity.

DimensionReasoningScore

Conciseness

Mostly efficient command tables, but ~540 lines with notable redundancy (session/auth/color-scheme covered multiple times) and some explanatory padding means not every token earns its place.

2 / 3

Actionability

Provides fully executable, copy-paste bash commands with exact flags and real ref examples throughout, matching the top anchor for concrete executable guidance.

3 / 3

Workflow Clarity

Core Navigate→Snapshot→Interact→Re-snapshot flow is clearly sequenced with ref-lifecycle warnings, but destructive/batch operations (auth, state) lack consistent explicit validate→fix→retry feedback loops.

2 / 3

Progressive Disclosure

Has a signaled Deep-Dive reference table, but two of seven referenced files (commands.md, profiling.md) do not exist and large command/security content remains inline rather than split out.

2 / 3

Total

9

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is exemplary: it states concrete capabilities, gives natural trigger terms, covers both what and when explicitly, and occupies a distinct niche. It matches the strongest reference examples closely with no notable weaknesses.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps') rather than vague language, matching the top anchor.

3 / 3

Completeness

Explicitly answers both what ('Browser automation CLI for AI agents...') and when ('Use when the user needs to interact with websites...') with explicit triggers, matching the top anchor example.

3 / 3

Trigger Term Quality

Provides natural user phrasings ('open a website', 'fill out a form', 'click a button', 'take a screenshot', 'scrape data from a page') that users would actually say, giving good coverage.

3 / 3

Distinctiveness Conflict Risk

'Browser automation CLI for AI agents' paired with specific web-interaction triggers carves a clear niche unlikely to conflict with other skills.

3 / 3

Total

12

/

12

Passed

Validation

75%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation12 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (540 lines); consider splitting into references/ and linking

Warning

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

relative_links

Relative link issues: 5 missing

Warning

referenced_paths_exist

Referenced path issues: 4 missing

Warning

Total

12

/

16

Passed

Repository
rivet-dev/sandbox-agent
Reviewed

Table of Contents

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