lambda-lang
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.
Best use case
lambda-lang is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using lambda-lang should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/lambda-lang/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How lambda-lang Compares
| Feature / Agent | lambda-lang | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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.
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