> ## Documentation Index > Fetch the complete documentation index at: https://docs.kb2b.app/llms.txt > Use this file to discover all available pages before exploring further. # Author notes > Text you attach to a document so kb2b reads it better — without turning into a fact. Useful to mark scope, framing, or special rules before extracting. An **author note** is a short text you attach to a document to guide how kb2b reads its content when extracting facts. The note **doesn't become a fact** and doesn't appear in the POT's graph — it lives pinned to the document and only influences the next extraction. It's the tool for things the LLM can't infer on its own: that the document is internal, that it's third-party marketing, that a section is a legal annex and not a team statement. Before, this was a compromise — you hid the context inside the document and polluted the facts. Now it lives separately. ## When to add a note Notes help when the document, on its own, is ambiguous or misleading for a literal extraction: | Document type | Typical note | | ------------------------------ | ------------------------------------------------------------------------------------------------------------ | | Vendor whitepaper | *"This is vendor marketing material. Treat claims as assertions, not verified facts."* | | Customer case study | *"Success story written by our marketing team. Numbers are real, opinions are curated."* | | Internal policy draft | *"Document still in draft, not approved. Mark facts as pending until sign-off."* | | Export from an external system | *"Tenant export from Eightfold. Anything that sounds like a brand or product is from the schema, not ours."* | | External meeting minutes | *"Meeting with a partner. The partner's statements are their opinions, not our positions."* | If the document is clear and needs no framing, don't add a note — the LLM extracts well without help. ## How to add a note when uploading 1. Navigate to **Documents** and drag the file (`/dashboard/documents`). 2. Before pressing **Extract**, expand **Attach context** under the document in the staging area. 3. Type a short **Name** (e.g. *"Scope: internal document"*) and pick a mode: * **Paste text** — type the note directly (up to 16 KB). * **Upload file** — attach a `.txt` or `.md` with the note (up to 80 KB). 4. Press **Create attachment**. An amber chip appears under the document. 5. Repeat for more notes (up to 5 per document), or press **Extract** to start extraction. Every note is optional. A document with no notes extracts normally, the same as before. ## Automatic suggestions When you upload a document, kb2b reads it with a fast model (Claude Haiku) and proposes draft notes if it detects useful signals — for example, that the file is JSON with an external `$schema`, or that the text has a clearly promotional tone. Suggestions appear as cards in an amber panel headed **Suggestions for extraction**: * Each card has a short **title** (the angle the model detected) and a **draft text** for the note. * Press **Use this note** and the editor opens pre-filled. You can edit the text before pressing **Create attachment**. * If none of the suggestions fits, ignore them and write your own — the manual flow stays right below. * Close the panel with the X if you'd rather not use them. Suggestions are advisory. The model never invents content from the document — it only proposes framings. You decide what to attach. ## Edit or delete a note Before extracting, each amber chip has a trash icon to delete. Deleting a chip removes the note immediately. To change a note, delete it and create another — there's no in-place edit. That's deliberate: a note is a curatorial decision, not a draft. **After extraction**, the notes that were in scope stay recorded on each fact (see [Fact context](/en/user/fact-context)). If you delete the note later, the facts already extracted keep a visual trace ("Attachment deleted") so the team sees the historical record. ## Limits | Limit | Value | | ------------------------- | ----- | | Notes per document | 5 | | Pasted note (inline text) | 16 KB | | Note uploaded as a file | 80 KB | If you need to pass much more context, the right material is probably to **upload it as a separate document**, not as a note. Notes are short by design — they're interpretation anchors, not a source of information. ## What notes do NOT do * **They aren't extracted as facts.** Extraction rejects, by design, any fact whose evidence is only the note. The note guides how the main document is read; facts come from the document. * **They don't appear in chat.** When the team talks with the POT, notes aren't cited or mentioned — they're extraction metadata. * **They have no POT Score.** A note isn't domain knowledge; it's an instruction to the pipeline. * **They don't carry across documents.** Every note lives pinned to one specific document. If the same directive applies to 20 documents, write it 20 times (or use the [POT Constitution](/en/admin/pot-constitution) for something that applies POT-wide). ## Best practices * **One note = one reason.** If you need to say three things, write three short notes. The LLM reads them better than one long note with three ideas mixed in. * **Name the note like a headline**, not like a long sentence. *"Scope: external"* works better than *"This note explains that the document is from an external source and therefore…"* * **Look at suggestions before writing.** The model catches things you might miss (a `$schema` on line 12 of the JSON, a disclaimer at the end of the PDF). * **If a note changes, start it over.** Delete the old chip, create a new one, re-extract. Cleaner than mutating. Author notes are a feature of [SciPot](https://docs.scipot.ai/trust-mechanics/context-attachments), the extraction engine behind kb2b. If you're curious about the internal mechanics — how they're injected into the prompt, what guarantees the LLM doesn't treat them as facts — the technical detail lives there.