Clickhouse Js Node Rowbinary logo

Clickhouse Js Node Rowbinary

Organization
ClickHouse
clickhouse-js-node-rowbinary

Generate TypeScript/JavaScript code that reads/decodes AND writes/encodes ClickHouse RowBinary streams for the ClickHouse HTTP server. Use this skill whenever a user wants to parse or produce `RowBinary`, `RowBinaryWithNames`, or `RowBinaryWithNamesAndTypes`. Node.js only, doesn't cover browsers.

Overview

PublisherClickHouse
Repositoryagent-skills
Skill nameclickhouse-js-node-rowbinary
Stars
543
Forks
39
Bundled files
190
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 190 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ClickHouse on GitHub. Read the source before you install it.

Installation

Install the Clickhouse Js Node Rowbinary AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ClickHouse/agent-skills/tree/main/skills/clickhouse-js-node-rowbinary
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ClickHouse/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/clickhouse-js-node-rowbinary .claude/skills/clickhouse-js-node-rowbinary
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Clickhouse Js Node Rowbinary in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Clickhouse Js Node Rowbinary on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Clickhouse Js Node Rowbinary is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ClickHouse JS RowBinary Codec Generator for Node.js

This skill generates both directions of the wire format: readers (decode bytes → values) and writers (encode values → bytes, the mirror). A given task normally needs only one side. This file is the shared entry point — the format gate plus the principles common to both directions; the per-direction decisions, guidance, and the per-type reference tables live in two sibling files.

Pick your side — read only the one you need:

  • Decoding a RowBinary* response from ClickHouse into JS values → reader.md. Streaming vs whole-buffer, row-objects vs columnar, fixed vs runtime schema, and the per-type reader reference.
  • Encoding JS values into a RowBinary payload to send to ClickHouse → writer.md. The Sink/writeX building blocks, writeRows streaming, and the per-type writer reference.

The per-type code is real, split by direction under src/readers/ and src/writers/.

First: is RowBinary even the right format?

RowBinary exists for throughput, but it is not automatically the fastest path — match the format to the shape of the data before committing to a bespoke parser.

Prefer a JSON* format (e.g. JSONEachRow) when the result is mostly strings / JSON-like values that you consume wholesale — randomly accessing essentially every field, running string/regexp methods on them, treating values as text. V8's native JSON.parse is heavily optimized C++ and builds JS strings and objects faster than a JS-level RowBinary decoder can; pair it with HTTP response compression (gzip / zstd, which crushes JSON's repetitive keys) and the wire cost shrinks too.

RowBinary clearly wins when the result is dominated by:

  • Wide numerics — Int128/Int256/UInt128/UInt256, Decimal128/Decimal256.
  • Binary / fixed-width blobs — IPv4, IPv6, UUID, FixedString.
  • High-volume fixed-width numeric columns generally, where each value is a single DataView read.

Prefer the Native format when columnar load and client-side analytics are the main goal (fold/scan/filter columns, feed typed arrays to a Worker or WASM). Native is column-major, so it loads straight into one typed array per column with no transpose.

For help choosing and consuming a JSON* format (or CSV / TSV) instead, use the clickhouse-js-node-coding skill.

Core guidance (both directions)

These principles apply whether you are generating a reader or a writer; the side-specific operational guidance is in reader.md / writer.md.

  • Little-endian only. RowBinary is little-endian; target x86/ARM. Read and write every multi-byte number with DataView accessors passing a literal true for the littleEndian flag.

  • Correct first, then optimize. First emit a correct codec built from the plain per-type API. Only after it's correct (and tested) specialize it. Don't bake performance assumptions in before correctness.

  • Monomorphize generic/composite types. Emit specialized, inlined code per type combination instead of passing functions as arguments where the type is known ahead of time.

  • Inline the leaf ops. The per-type readX/writeX functions are the correct, composable reference; the generated codec should INLINE their bodies, not call them, so the row loop is straight-line with no per-field indirection (and so the fixed-width coalescing can fold the offset arithmetic together).

  • Annotate the type per column. Inlining erases the type structure, so put a short comment above each column's encode/decode block naming the ClickHouse type it handles.

  • Shared scratch is not reentrant. Some hot methods reuse a module-level scratch buffer as a write-then-read pair — correct only because the access is fully synchronous. An async/yield boundary between populating and reading it corrupts the value.

  • TypeScript by default. Generate TypeScript code and helpers unless the user explicitly asks for plain JavaScript.

Worked examples

Six end-to-end examples with real speedup are catalogued in EXAMPLES.md.

Out of scope

  • JSON / CSV / TSV / Parquet parsing → use clickhouse-js-node-coding.
  • Connection errors, hangs, type mismatches → use clickhouse-js-node-troubleshooting.
  • Browser / Web Worker / Edge → @clickhouse/client-web.

Still Stuck?

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 130 more files.

Frequently asked questions

What does the Clickhouse Js Node Rowbinary AI skill do?

Generate TypeScript/JavaScript code that reads/decodes AND writes/encodes ClickHouse RowBinary streams for the ClickHouse HTTP server. Use this skill whenever a user wants to parse or produce `RowBinary`, `RowBinaryWithNames`, or `RowBinaryWithNamesAndTypes`. Node.js only, doesn't cover browsers.

Why use Clickhouse Js Node Rowbinary on TypingMind?

Because you install it once and use it with any model. Clickhouse Js Node Rowbinary is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Clickhouse Js Node Rowbinary in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ClickHouse/agent-skills/tree/main/skills/clickhouse-js-node-rowbinary. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Clickhouse Js Node Rowbinary?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Clickhouse Js Node Rowbinary?

As many as you like. As long as a model supports skills, you can use Clickhouse Js Node Rowbinary with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Clickhouse Js Node Rowbinary AI skill free?

Yes. It is published on GitHub by ClickHouse under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇