Base44 SDK
Trusted74/100The base44 SDK is the library to communicate with base44 services. In projects, you use it to communicate with remote resources (entities, backend functions, ai agents) and to write backend functions. This skill is the place for learning about available modules and types. When you plan or implement a feature, you must learn this skill
Trust score 74/100 (Trusted) · 66+ installs · 11 GitHub contributors · MIT license
Developers building on the Base44 platform need to remember Base44 SDK's unique method names and tend to hallucinate APIs out of Firebase or Supabase habits. This skill provides wrong-vs-correct tables and pointers to per-module references so features are written correctly the first time.
How to use this skill
Not sure how? Read the guideThis is a community skill from an external source. The ZIP upload may not work on all platforms if the SKILL.md format is not fully compatible.
- 1. Click "Download ZIP" to download the skill files.
- 2. Open Claude Desktop and go to Customize > Skills.
- 3. Click "+" and select "Upload a skill", then upload the ZIP file.
- 4. Start a new conversation. The skill will activate automatically when relevant.
Developers? Install via command line (CLI)
npx skills-il add base44/skills -a claude-codeWhen to Apply
- Building a feature in an existing Base44 project that already has `base44/config.jsonc`
- Writing client code with `@base44/sdk` against entities, auth, integrations, or functions
- Authoring a backend function with `Deno.serve` and `createClientFromRequest(req)`
- Deciding between user mode and `asServiceRole` for admin operations
- Verifying SDK method names before invoking them
Try These Prompts
In my Base44 app, create a new task with title 'New doc' and status 'pending', then list all pending tasks.
In a Base44 external client, add an email-and-password login flow and fetch the current user.
From the frontend, invoke the 'processOrder' backend function with orderId='123' and action 'ship'.
Write a Deno backend function that receives an orderId, fetches the order via asServiceRole, and returns a JSON response.
Frequently Asked Questions
Related Skills
Guide developers in integrating Israeli agritech tools and precision agriculture platforms including CropX (soil monitoring), Netafim GrowSphere (IoT irrigation), Taranis (crop intelligence), and the broader Israeli agritech ecosystem (approximately 600-750 companies per Start-Up Nation Central agrifoodtech). Use when user asks about agritech APIs, precision agriculture, smart irrigation, "hashkaya cham", crop monitoring, pest detection, Israeli agriculture tech, or needs to build farm management software. Covers irrigation optimization, pest detection, climate data integration, and Israeli agricultural context. Do NOT use for general gardening advice or non-agricultural IoT projects.
Compare cloud hosting costs for Israeli startups and developers across AWS (il-central-1 Tel Aviv), Azure (Israel Central), GCP (me-west1 Tel Aviv), Oracle Cloud (il-jerusalem-1 Jerusalem), and Israeli providers like Kamatera. Use when the user needs to evaluate cloud pricing with Israel-specific considerations including data residency under Privacy Protection Law Amendment 13, latency from Tel Aviv, NIS billing options, startup credit programs (AWS Activate, Google for Startups, Microsoft Founders Hub, Israel Innovation Authority Telem program with subsidized Nvidia B200 GPUs), and FinOps cost optimization strategies. Do NOT use for comparing on-premise hosting, colocation services, or non-cloud SaaS pricing.
Benchmark and compare LLMs on Hebrew reasoning, comprehension, sentiment, translation, and Israeli cultural knowledge. Wraps the HuggingFace Open Hebrew LLM Leaderboard tasks (HeQ, HebrewSentiment, Hebrew Winograd, translation) plus DictaLM 3.0 benchmark tasks (Summarization, Nikud, Israeli Trivia) into a reproducible evaluation harness. Runs evals against Claude, GPT, Gemini, AI21 Jamba, DictaLM, Llama, and local HuggingFace models. Produces comparison scorecards in JSON and markdown. Use when choosing an LLM for a Hebrew product, answering procurement questions about Hebrew performance, validating a fine-tuned Hebrew model, or tracking Hebrew regressions after a model upgrade. Do NOT use for Arabic NLP, ASR benchmarking, or general English benchmarks.
Use at your own risk. Terms of Use · Security
Want to build your own skill? Try the Skill Creator · Submit a Skill