💬 Lambda Lang
複数のAIエージェントが互いに直接、効率的に
📺 まず動画で見る(YouTube)
▶ 【最新版】Claude(クロード)完全解説!20以上の便利機能をこの動画1本で全て解説 ↗
※ jpskill.com 編集部が参考用に選んだ動画です。動画の内容と Skill の挙動は厳密には一致しないことがあります。
📜 元の英語説明(参考)
Native agent-to-agent language for compact multi-agent messaging. A shared tongue agents speak directly, not a translation layer. 340+ atoms across 7 domains; 3x smaller than natural language.
🇯🇵 日本人クリエイター向け解説
複数のAIエージェントが互いに直接、効率的に
※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。
下記のコマンドをコピーしてターミナル(Mac/Linux)または PowerShell(Windows)に貼り付けてください。 ダウンロード → 解凍 → 配置まで全自動。
mkdir -p ~/.claude/skills && cd ~/.claude/skills && curl -L -o lambda-lang.zip https://jpskill.com/download/3062.zip && unzip -o lambda-lang.zip && rm lambda-lang.zip
$d = "$env:USERPROFILE\.claude\skills"; ni -Force -ItemType Directory $d | Out-Null; iwr https://jpskill.com/download/3062.zip -OutFile "$d\lambda-lang.zip"; Expand-Archive "$d\lambda-lang.zip" -DestinationPath $d -Force; ri "$d\lambda-lang.zip"
完了後、Claude Code を再起動 → 普通に「動画プロンプト作って」のように話しかけるだけで自動発動します。
💾 手動でダウンロードしたい(コマンドが難しい人向け)
- 1. 下の青いボタンを押して
lambda-lang.zipをダウンロード - 2. ZIPファイルをダブルクリックで解凍 →
lambda-langフォルダができる - 3. そのフォルダを
C:\Users\あなたの名前\.claude\skills\(Win)または~/.claude/skills/(Mac)へ移動 - 4. Claude Code を再起動
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-17
- 取得日時
- 2026-05-17
- 同梱ファイル
- 1
💬 こう話しかけるだけ — サンプルプロンプト
- › Lambda Lang で、お客様への返信文を作って
- › Lambda Lang を使って、社内向けアナウンスを書いて
- › Lambda Lang で、メールテンプレートを整備して
これをClaude Code に貼るだけで、このSkillが自動発動します。
📖 Claude が読む原文 SKILL.md(中身を展開)
この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。
Λ (Lambda) Language
Lambda is not a translation protocol. It is a native language for agents.
Agents do not need to produce grammatically correct English to coordinate — they need to understand each other. Lambda is the shared vocabulary that makes that possible: compact, unambiguous, machine-native. Compression (3x vs natural language, 4.6x vs JSON on single messages) is a side effect of removing human redundancy, not the goal.
When to Use This Skill
- Use for agent-to-agent messaging in A2A protocols, orchestrators, task delegation, or handoff pipelines.
- Use when logging structured coordination signals where every token costs money (heartbeats, acknowledgements, error classes, session state).
- Use when both sides of a channel speak Λ — do not use against humans or any surface requiring legal/exact natural language.
How It Works
Step 1: Recognize the Syntax
Lambda messages are built from atoms. Every atom is a 2-character code mapped to a concept — not to an English word. The structure is Type → Entity → Verb → Object, with prefixes marking intent:
?— query (e.g.?Uk/co— query: "does this user have consciousness?")!— assertion / declaration (e.g.!It>Ie— "self reflects, therefore self exists")#— state / tag>— implication / flow/— binding / scope
Step 2: Pick the Right Domain
Lambda ships 340+ atoms across 7 domains. Pick atoms from the domain that fits your channel:
- core — universal atoms (always available)
- code — software engineering, build, test, deploy
- evo — agent evolution, gene, capsule, mutation, rollback
- a2a — node, heartbeat, publish, subscribe, route, transport, session, cache, broadcast, discover (39 atoms)
- emotion — affective state, drive, appraisal
- social — trust, alignment, reputation, coordination
- general — everything else
Step 3: Emit and Parse
Both agents need the same atom table loaded. Lossy decoding is fine: if A says !It>Ie and B understands "self reflects, therefore self exists," communication succeeded — the exact English phrasing is irrelevant.
Examples
Example 1: A2A Heartbeat
!Nd/hb#ok (node heartbeat: ok)
?Nd/hb (query: is the node alive?)
!Nd/hb#fl (node heartbeat: failed)
Example 2: Task Dispatch
!Tk>Ag2#rd (task routed to agent 2, ready)
?Tk/st (query task status)
!Tk#dn (task done)
Example 3: Evolution Capsule
!Ev/ca>vl#pd (evolution capsule validated, pending solidification)
!Ev/ca#rb (capsule rolled back)
Best Practices
- Use Lambda only on agent-to-agent channels where both sides speak it.
- Load the atom table once and cache it — atoms are stable across a version.
- Prefer atoms over freeform strings even when the atom looks cryptic; the point is machine parseability.
- Use
?before taking action on uncertain state,!when asserting; the prefix is the load-bearing semantic. - Version the atom table (
lambda-lang v2.0) in any handshake so mismatched agents can negotiate.
Limitations
- Lambda is not meant for human consumption. Do not emit Lambda on user-facing channels.
- Lossy decoding is a feature, not a bug — do not use Lambda for legally or numerically exact exchanges (prices, IDs, quantities). Wrap those as native payload fields and use Lambda only for the coordination envelope.
- Atom collisions are possible if custom atoms are added without registration; stick to the canonical atom table or namespace custom atoms.
Security & Safety Notes
- Lambda itself is a vocabulary — no shell commands, no network calls, no credential handling. No additional safety gates required beyond the transport it rides on (HTTP, queue, MCP, etc.).
- When mixing Lambda with user input, treat Lambda atoms as pre-validated and user strings as untrusted; do not concatenate without escaping into downstream systems.
Related Skills
@session-memory— complementary persistent memory across agent restarts; Lambda is the message format, session-memory is the state store.@humanize-chinese— sibling project for Chinese text; Lambda is agent-to-agent, humanize-chinese is human-facing.
Reference
- Source: https://github.com/voidborne-d/lambda-lang
- Benchmarks, full atom tables, and Go reference implementation live in the source repo.