Plan a Trekking Trip With AI, a Weight Spreadsheet, and the LighterPack SDK

A developer detailed a workflow for planning trekking trips using AI, a weight spreadsheet, and the unofficial LighterPack SDK. The approach structures planning into three layers—planning, inventory, and publishing—with AI assisting in drafting checklists and extracting data from invoices, while the CSV remains the deterministic source of truth. The developer emphasized reviewing AI outputs for accuracy and treating credentials securely.

Planning a multi-day trek is a data problem disguised as an adventure. You collect GPX files, weather notes, permit links, and a growing pile of gear receipts. Weight limits show up in airline rules, in your own fitness goals, and in every "do I really need this?" moment at 4,000 meters. Most hikers end up with the same fragmentation: a spreadsheet here, a LighterPack list there, product links in browser tabs, and half-remembered weights copied from store pages. The list gets stale the moment you buy one more layer or swap a stove. This tutorial describes a workflow I used while preparing a Salkantay trek repository, generalized so you can adapt it to any hike. The idea is simple: @paladini/lighterpack You will not get a magic "upload PDF → perfect pack list" button. You will get a repeatable pipeline you can version in Git, re-run before a trip, and extend with your own rules. Think in three layers: | Layer | Role | Artifact | |---|---|---| | Planning | Context, route, references | README.md , GPX, notes | | Inventory | Quantities, weights, prices, purchase status | gear/items.csv | | Publishing | Shareable pack list with categories and photos | LighterPack list + public link | AI sits on the edges of this system: helping you draft the plan, extracting rows from invoices, and filling gaps when a product page is hard to parse. The CSV stays deterministic. The sync script stays boring. That separation is what makes the workflow trustworthy. 2026/my-trek/ .The SDK is unofficial . It talks to the same web API the LighterPack site uses and authenticates with your normal username and password. Treat those credentials like any other secret. Start with questions AI is good at when you feed it structured context: Ask for a draft checklist by category shelter, cooking, clothing, safety , not a final weight table. Your job is to reject, merge, and annotate. A useful prompt pattern: I am hiking trail in month with N people. Constraints: weight limit , diet , owned vs to-buy . Return a table with columns: category, item, model, quantity, notes. Mark each row as owned, to-buy, or borrow. Do not invent weights or prices. Save the narrative plan in README.md and keep evolving it. Do not let the chat transcript become your inventory database. Chats are great for exploration; they are poor as source of truth. This is where AI saves the most tedious work. After you buy gear, you usually have: Paste the text or attach a readable PDF/image and ask the model to emit CSV-shaped rows aligned with your schema. Recommended columns: category,item,model,quantity,unit price,total price,unit weight kg,total weight kg,baggage,status,notes,url Example prompt: Extract gear purchases from this invoice into CSV rows. Schema: category,item,model,quantity,unit price,total price,unit weight kg,total weight kg,baggage,status,notes,url Rules: - baggage is "carry-on" or "checked" when known, else empty. - status is "owned", "to-buy", or "rent". - unit weight kg only if explicitly stated; otherwise leave blank. - url: product page if visible, else empty. - One row per line item; quote fields that contain commas. Output only CSV, no commentary. Review every row. AI will misread bundles "2 pairs of socks" vs quantity 2 , confuse shipping with product weight, and hallucinate URLs. Weights from manufacturer pages are often missing on invoices — look them up once, then store them in the CSV. For a two-person trip, decide early whether quantities are per person or shared and document that in notes . LighterPack supports quantity per line item; your spreadsheet should match how you think about the pack. Once reviewed, commit gear/items.csv to Git or keep it locally if you prefer . This file is the contract between: Conventions that paid off in practice: Camping , Clothing , Hydration , etc. . Math.round kg 1000 .A minimal row might look like: Clothing,Trekking boots,Hoka Speedgoat 6,2,1000.0,2000,0.267,0.534,carry-on,owned,, Install the SDK: npm install @paladini/lighterpack Create scripts/lighterpack/.env never commit it : LIGHTERPACK USERNAME=your username LIGHTERPACK PASSWORD=your password The sync script reads the CSV, groups items by category, resolves images, and creates the list in one batch call. The core pattern: js import { LighterPackClient } from '@paladini/lighterpack'; const lp = new LighterPackClient { username: process.env.LIGHTERPACK USERNAME , password: process.env.LIGHTERPACK PASSWORD , } ; await lp.account.setCurrencySymbol '$' ; // or €, £, etc. const detail = await lp.batch.createListWithItems { name: 'My Trek 2026 2 people ', description: 'Generated from gear/items.csv', categories: { name: 'Shelter', items: { name: '2-person tent', description: 'Naturehike Star River 2 · Checked bag', qty: 1, weight: 1950, // grams weightUnit: 'g', price: 900, url: 'https://example.com/tent', worn: false, consumable: false, }, , }, , } ; await lp.lists.setOptionalFields detail.listId, { images: true, price: true, worn: true, consumable: true, packWeight: true, } ; const shareUrl = await lp.lists.generateShareLink detail.listId ; console.log shareUrl ; createListWithItems is the workhorse: one round trip to scaffold categories and items. For large lists 50+ lines , this is far less fragile than clicking through the UI. Map CSV columns to SDK fields explicitly: name ← item description ← model , notes , baggage , status joined as readable text qty ← quantity weight ← unit weight kg converted to grams price ← unit price url ← url LighterPack can display item photos from external URLs, but retailer CDNs often block hotlinking or return generic Open Graph images. In a real sync of ~50 items, a majority of naive og:image URLs failed. A more reliable approach: lp.items.uploadImage itemId, { buffer, filename, mimeType } .Local upload beat setImageUrl for visibility on the share page. Keep downloaded binaries out of Git; store only the resolver map and scripts. After npm run sync:trek or your own script name , check: Example output from a successful run: { "listId": 17, "name": "Salkantay 2026 2 people ", "weightGrams": 25100, "price": 14489.78, "shareUrl": "https://lighterpack.com/r/example" } Re-run the sync after CSV edits. Idempotency strategy: find an existing list by name, delete it, recreate. Crude but clear for personal repos. .env , passwords, or invoice PDFs with personal data.| Choice | Benefit | Cost | |---|---|---| | CSV as source of truth | Git-diffable, scriptable | Manual review after AI extraction | | Batch SDK create | Fast, repeatable | Deletes/recreates list on full sync | | AI invoice parsing | Less typing | Requires validation; not fully autonomous | | Local image upload | Reliable thumbnails | Extra download/upload step | This workflow is optimized for multi-day treks where gear lists are large and shared. For a day hike, a single LighterPack list edited by hand is probably enough. make check that validates CSV totals and required fields before sync.If you try this pipeline, start with ten items end to end before importing a full expedition list. Fix the schema once, then scale. Question for readers: Where do you draw the line between "AI drafts the row" and "I require a photo of the scale / spec sheet before it enters the CSV"? I still hand-verify every weight that affects carry-on compliance. @paladini/lighterpack on npm