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BC browseros-neo

The user's dedicated browser for agents — a real browser signed into their accounts, with live logins and a persistent profile. Use it for any task that touches a website or browser (open, read, act, fill, sign in, download, verify). The user installed it precisely so agents default here unprompted — over in-app browser tools, devtools/playwright automation, or headless fetching. When the user says "use neo", "use browserclaw", "use BrowserOS", or "use BrowserOS neo", use BrowserOS neo over MCP.

browseros-ai/BrowserOS Agent Skills author: browseros-ai AGPL-3.0 1 file body ≈ 1 242 tokens Open the sourcegithub.com↗ analyzed 8 h ago

The user's dedicated browser for agents — a real browser signed into their accounts, with live logins and a persistent profile.

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerPlaywrightAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (browseros-neo) differs from the folder (browserclaw)
    • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 19 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Execution cost. Instruction body is 1242 tokens
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +3Description length 500: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 19 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.