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browser-use-integration

Self-hosted AI browser automation using Browser Use with any LLM (Claude, GPT, Ollama). Use when building web scraping agents, data extraction pipelines, self-hosted automation, or when you need flexibility without API rate limits.

Quality

70%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/browser-use-integration/SKILL.md

The canonical home for this skill is browser-use-integration in fernandezbaptiste/Skrillz

SKILL.md
Quality
Evals
Security

Quality

Content

46%Weight 40%Scale 1-5

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 concrete, runnable code for setup, agent patterns, error handling, and Docker self-hosting, but it is bloated with duplicate examples, redundant provider configuration, and marketing padding. More critically, its reference links point to files that do not exist while the real bundle files go unlinked, and batch/form workflows lack validation steps.

Suggestions

Fix the References section to link the actual bundle files: replace `references/browser-use-setup.md` and `references/llm-configuration.md` (which do not exist) with `references/api-reference.md` and `references/wsl2-setup.md`, and surface the WSL2 guide prominently since it covers a common platform failure mode.

Trim the five near-duplicate Use Cases to one or two representative examples and move the three-provider LLM configuration details and cost table into a reference file to cut the body roughly in half.

Add a verification checkpoint to the batch data-entry and form-submission workflows (e.g., confirm each submitted result or re-read the saved record before proceeding) so failures are caught mid-loop instead of after the batch.

DimensionReasoningScore

Conciseness

The ~515-line body contains several padded sections Claude does not need: marketing bullets ("3-5x Faster", "No vendor lock-in"), five near-duplicate Use Cases repeating `agent = Agent(task=..., llm=llm); result = await agent.run()` roughly ten times, full three-provider LangChain configuration Claude already knows, and a time-sensitive cost table with pinned model versions. This matches the score-2 anchor (noticeably verbose, several unnecessary sections) rather than the mostly-efficient score-3 anchor.

2 / 5

Actionability

Guidance is mostly executable and copy-paste ready: install commands, a runnable quick-start agent, `output_schema` structured extraction, retry with exponential backoff, and complete Dockerfile/docker-compose files. Not 5 due to minor gaps: `os.environ` is used without `import os`, `llm` is undefined in later examples, and `browser.load_cookies`/`AgentError` are unverified APIs.

4 / 5

Workflow Clarity

The quick start is a clear four-step sequence (install, configure key, write agent, run) and error-handling patterns exist, but there are no validation checkpoints, and the batch data-entry loop and form-submission workflows run with no verification step. Per the rubric's cap for batch operations lacking validation, workflow clarity is capped at 3.

3 / 5

Progressive Disclosure

The References section points to `references/browser-use-setup.md` and `references/llm-configuration.md`, neither of which exists in the bundle, while the actual files (`references/api-reference.md`, `references/wsl2-setup.md`) are never linked — including the WSL2 setup guide covering a critical platform gotcha. Combined with setup/API detail inlined in the body that belongs in those reference files, this matches the score-2 anchor (references buried or broken, separable content inlined) rather than the score-3 anchor of present-but-unclear references.

2 / 5

Total

11

/

20

Passed

Description

83%Weight 40%Scale 1-5

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 strong: it clearly states what the skill does and when to use it, with natural trigger terms and a distinct Browser-Use/self-hosted niche. Minor improvements would add missing synonyms (web automation, form filling) and sharpen distinctiveness from generic scraping or LLM-setup skills.

DimensionReasoningScore

Specificity

"Self-hosted AI browser automation using Browser Use with any LLM (Claude, GPT, Ollama)" names the domain and lists several concrete actions/contexts ("web scraping agents, data extraction pipelines, self-hosted automation"), matching the several-specific-actions anchor with minor gaps (form automation, testing use cases absent). Not 3 because coverage exceeds 1-2 actions; not 5 because some verbs remain generic and use-case coverage is incomplete.

4 / 5

Completeness

It explicitly answers both: what ("Self-hosted AI browser automation using Browser Use with any LLM") and when ("Use when building web scraping agents, data extraction pipelines, self-hosted automation, or when you need flexibility without API rate limits"), with concrete trigger phrases matching the score-5 anchor.

5 / 5

Trigger Term Quality

Natural user phrases like "browser automation", "web scraping", "data extraction", "self-hosted", and "API rate limits" give good keyword coverage per the score-4 anchor. Not 5 because common synonyms such as "web automation", "form filling", or framework-alternative terms are missing.

4 / 5

Distinctiveness Conflict Risk

The named framework "Browser Use" plus the self-hosted/Ollama angle creates a mostly distinct niche, but "any LLM (Claude, GPT, Ollama)" and "flexibility without API rate limits" introduce minor overlap risk with general scraping or LLM-configuration skills, matching the score-4 anchor rather than a fully distinct score-5 profile.

4 / 5

Total

17

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (521 lines); consider splitting into references/ and linking

Warning

referenced_paths_exist

Referenced path issues: 2 missing

Warning

Total

14

/

16

Passed

Repository

fernandezbaptiste/Skrillz

Path

.claude/skills/browser-use-integration/SKILL.md

Reviewed

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