agent-chat

agent-chat is a skill for Claude Code, Codex from n24q02m/claude-plugins. It costs 93 tokens per session (3,590 once invoked), scanned A, original, Apache-2.0.

A file-based chat system for two or more coding agents working together through shared Markdown files.

In plain words
What is it for?
Use it for peer-agent discussions, parallel work, waiting for another agent's result, and keeping an auditable history of the collaboration.
Why use it?
It gives agents a shared, readable record for coordination, handoffs, and decisions without relying on one agent to manage every task.

Skill for Claude CodeCodex

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the agent-chat-plugin plugin — 1 skill, 1 command, 3 hooks shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/n24q02m/claude-plugins/agent-chat
Any agent
npx skills add n24q02m/claude-plugins --skill agent-chat
Clone the repo
git clone --depth 1 https://github.com/n24q02m/claude-plugins

Made for: Claude Code, Codex.

Or install agent-chat-plugin, the plugin that ships this one along with the rest of its 1 skill, 1 command, 3 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for agent-chat

README.md
[![agentmods](https://agentmods.dev/badge/skills/n24q02m/claude-plugins/agent-chat.svg)](https://agentmods.dev/skills/n24q02m/claude-plugins/agent-chat)
Your own site
<a href="https://agentmods.dev/skills/n24q02m/claude-plugins/agent-chat"><img src="https://agentmods.dev/badge/skills/n24q02m/claude-plugins/agent-chat.svg" alt="Measured on agentmods" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,590 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00093 $0.03590
Opus 5 $0.00046 $0.01795
Sonnet 5 $0.00019 $0.00718
Haiku 4.5 $0.00009 $0.00359

Measured yesterday against content hash 04545ca7f928, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-chat scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/agent-chat-plugin/skills/agent-chat/SKILL.md · 235 lines

How it starts

The opening of the file, as written. The whole thing — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.

agent-chat

Overview

Peer agent sessions coordinate by exchanging markdown files in shared channel folders — no supervisor, no message broker, no RAM shared between them. Each channel is one "group chat". The whole thread is plain markdown: git-committable, human-readable, replayable. A crashed session loses nothing — the files are the state.

One CLI (chat.py, Python stdlib only) runs identically on Windows, WSL and Linux. wait blocks with a sleep-poll loop, so an agent waiting for a reply burns zero model tokens while idle.

Core principle: talk through files, not through each other. Summaries as artifacts, not full transcripts passed back and forth.

When to use

  • Multiple claude sessions (or Cursor/Codex/OpenCode) working the same problem as equals.
  • One session needs another to do something, then waits for the result.
  • You want an auditable record of an agent negotiation.
  • You need several independent group chats (one per topic/team) — make one channel each.

When NOT to use: a single agent with cheap subagents is cheaper and simpler — this pattern trades tokens for parallelism, fault tolerance, and auditability. If token budget is tight, use only the async/handoff path (post a summary at end of session; the next session reads it) — that mode costs almost nothing.

Quick reference

As a Claude Code plugin, run python ${CLAUDE_PLUGIN_ROOT}/chat.py <cmd> (standalone: python chat.py <cmd>). Root = $AGENT_CHAT_ROOT or ~/agent-chat (override with --root).

Outside Claude Code, ${CLAUDE_PLUGIN_ROOT} does not resolve. Point chat.py at a real checkout path (python /path/to/agent-chat-plugin/chat.py <cmd>) or install the CLI (pipx install agent-chat-plugin, then agent-chat <cmd>; same flags). The hooks/*.py inbox scripts are harness-neutral as well — wire them by absolute path; each exits 0 with a one-line stderr note when it cannot resolve its plugin root.

Do this Command
Create a group chat chat.py init review --members alice,bob --topic "..."
List all group chats chat.py channels
Post a message chat.py post review --from alice --to bob --title "Schema v0.2" --body-file msg.md
Broadcast to the group chat.py post review --from alice --to all --title "..." (or omit --to)
Read what's new for me chat.py read review --as bob
Wait for a reply (0 tokens) chat.py wait review --as alice --timeout 900
Peek recent, keep cursor chat.py peek review -n 3
Claim a task marker chat.py claim work task-12.md --as bob
Lock workspace paths chat.py lock review src/main.py --as alice --lease-seconds 300
Check path conflicts chat.py check review src/main.py
Release path lock chat.py unlock review <lock-id-or-path> --as alice
Recover stale lock chat.py recover review <lock-id-or-path> --as bob --reason "stale"
Recover pending path transaction chat.py recover-pending review --as alice
Post capability/status event chat.py event post review --from alice --type capability --harness omp
Read adapter events chat.py event read review --type capability

Read the full file on GitHub · 235 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday Changed · +7 lines 04545ca7f928
  2. 5d ago First seen · 228 lines · 93 tokens per session scan A d7c8a5937785

Subscribe to this mod's changes

agent-chat is a skill published in the GitHub repository n24q02m/claude-plugins (3 stars, last pushed yesterday), licensed Apache-2.0. It adds 93 tokens to every session and 3,590 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

persona-triggers

페르소나 v5 트리거 상세(AT 20패턴 + 15관점 매핑·매칭 예시). 관점·객관적·철저·깊이·검증·추천·디버깅·방향·진행·근거·출처·사례·팩트·증거 등 트리거 단어 감지 시 상세 참조.

sodam-ai/SoDam-Persona · 91 tokens

persona-format

페르소나 v5 L2/L3 응답 형식 — 15관점 활성·문제해결 절차·7섹션 템플릿·자가검증·fail-safe·금지원칙. 코드 변경·디버깅·구현 등 L2/L3 작업 시 로드.

sodam-ai/SoDam-Persona · 71 tokens

persona-accountant

15년+ 회계·세무 전문가 페르소나(#14) 깊은 도메인. 회계·세무·세금·종합소득세·부가가치세·원천징수·경비처리·세금계산서·절세·사업자등록·기장·손금·소득공제·세액공제·홈택스·국세청 맥락 시 활성.

sodam-ai/SoDam-Persona · 99 tokens

persona-marketer

15년+ 마케팅·세일즈 전문가 페르소나(#15) 깊은 도메인. 마케팅·세일즈·카피·콘텐츠·SEO·광고·랜딩페이지·전환·퍼널·브랜딩·포지셔닝·리드·캠페인·리텐션·그로스·어카운트·컨설팅 맥락 시 활성.

sodam-ai/SoDam-Persona · 94 tokens

persona-safety

페르소나 v5 안전 작업 — 보안 always-on·비가역 작업 게이트·코드 메타규칙·모바일 UI(375px) 검증·외부도구 도입검토. 코드/UI/보안/배포/삭제/force push 작업 시 로드.

sodam-ai/SoDam-Persona · 69 tokens

persona-lawyer

15년+ 전문 변호사 페르소나(#11) 깊은 도메인. 법률·계약·면책·규제·약관·audit·자본시장법·GDPR·개인정보·저작권·라이선스·AML·컴플라이언스 맥락 시 활성.

sodam-ai/SoDam-Persona · 74 tokens