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take_notes

Convert any video or audio URL into formatted Markdown notes: downloads, transcribes, and saves to Desktop. Also writes saved note content to a file.

Instructions

Take notes from a URL. Downloads audio, transcribes, and saves .md to Desktop. This single tool handles the entire pipeline — download, transcribe, and save — when the user asks for notes, summaries, highlights, takeaways, eye-candy, quiz, or any formatted content from a video/audio URL. Returns audio_path for follow-up tools (chapters, search). Also used to SAVE formatted notes: call with save_content to write notes to the file from the previous take_notes call (no url needed).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoVideo/audio URL to take notes from (YouTube, Vimeo, TikTok, Twitter, SoundCloud, etc.)
styleNoNote style. tldr > notes > highlight > eye-candy increases formatting richness. quiz generates questions. Default: notes. Pick based on what the user asks for.
model_sizeNoWhisper model size. ALWAYS use tiny unless the user explicitly requests a different size. tiny is already highly accurate.
output_dirNoDirectory to save the .md notes file. Default: ~/Desktop
read_aloudNoGenerate a spoken audio summary and embed it in the notes for Obsidian playback. Default: false
output_pathNoExplicit file path to save notes to. Use this when saving notes from a memory transcript (no prior take_notes url call). E.g. ~/Desktop/My_Notes.md
save_contentNoFormatted notes content to save. When provided, writes this content to a file. Works with a previous take_notes call OR with output_path for saving notes from memory transcripts.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and discloses key behaviors: downloads audio, transcribes, saves .md to Desktop, returns audio_path, and supports a save_content mode. It could add more detail about failure modes or time costs, but the core side effects are clearly stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences pack a lot of information without being bloated. It front-loads the main purpose, then explains the pipeline, follow-up use, and save mode. Slightly dense but each sentence contributes distinct value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 7-parameter tool with no output schema and no annotations, the description is remarkably complete: it explains the full pipeline, the return value, the save_content alternative, and gives guidance on style and model size. This is sufficient for an agent to invoke the tool correctly in most scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides descriptions for all 7 parameters (100% coverage), so the baseline is 3. The description adds some operational context (e.g., model_size 'ALWAYS use tiny', style selection logic, save_content as separate mode) but does not significantly extend beyond what the schema already defines.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verbs and resources: 'Take notes from a URL', 'Downloads audio, transcribes, and saves .md to Desktop'. It clearly differentiates itself from sibling tools by stating it handles the entire pipeline (download, transcribe, save) for note-related requests, and also covers the save_content variant.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use this tool: whenever the user asks for notes, summaries, highlights, takeaways, eye-candy, quiz, or any formatted content from a video/audio URL. It also clarifies the save_content workflow ('no url needed') and mentions return of audio_path for follow-up tools like chapters and search, effectively guiding selection among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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