SKILLEMALL.ai
GitHub ↗ RU Sign in

AC notebooklm-login

Login to Google NotebookLM via Chrome DevTools Protocol and save auth cookies for notebooklm-mcp. Use when user asks to login, authenticate, or re-authenticate NotebookLM MCP, or when `nlm login --check` shows expired/missing credentials.

ClawHub Agent Skills author: ou-rock v1.0.0 MIT-0 3 files body ≈ 420 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting

ReferenceAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
99
Quality 40%
87
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:29
      Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
      If missing, install Chromium (`apt install chromium-browser`) and uv (`curl -LsSf https://astral.sh/uv/install.sh | sh`).
      quoted

    Files scanned: 3. 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 64/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 9 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 420 tokens
    • 100Running it twice. No mutating operations

    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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 238: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 9 items
    • +4Has examples (3 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: suspicious
    This skill appears to do what it claims, but it creates and stores reusable Google session cookies through a debug-enabled browser, so it needs careful review before use.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026