AB notebooklm-distiller
NotebookLM Distiller: Batch knowledge extraction from Google NotebookLM into Obsidian. Supports Q&A generation (15-20 deep questions), structured summaries, glossary extraction, web research sessions, and direct markdown persistence.
As a process B 69/100 · Nearly there — weak spots: when it triggers
AnalyzerObsidianDiscordLearningAI and agentstype and topics are labelled automatically from the skill text
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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "permissions"
Process rating: all ten parameters 69/100
- 20When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 42 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1601 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- low The response is described with custom markup (9 tags): a typed call is more reliable
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)
- +1No license
- +2Single-language instructions
- +3Description length 233: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 42 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.
External checks
ClawHub: suspicious
This skill matches its stated NotebookLM-to-Obsidian purpose, but it needs review because it can create NotebookLM resources and write or overwrite local notes without strong confirmation or path safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026