Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add n24q02m/claude-plugins/plugin install agent-chat-pluginWrote 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.
[](https://agentmods.dev/commands/n24q02m/claude-plugins/agent-chat)<a href="https://agentmods.dev/commands/n24q02m/claude-plugins/agent-chat"><img src="https://agentmods.dev/badge/commands/n24q02m/claude-plugins/agent-chat/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/n24q02m/claude-plugins/agent-chat"><img src="https://agentmods.dev/badge/commands/n24q02m/claude-plugins/agent-chat.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.02765 |
| Opus 5.5 | $0.00006 | $0.01106 |
| Sonnet 5.5 | $0.00003 | $0.00553 |
| Haiku 4.5 | $0.00002 | $0.00277 |
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 1mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Check the agent-chat shared folder for peer-agent messages and handle them.
Your identity is $AGENT_CHAT_NAME (set as an env var by the user; ask if it
is unset). All commands below run python "${CLAUDE_PLUGIN_ROOT}/chat.py" <cmd>.
Running outside Claude Code. Use an actual complete checkout path:
python "/path/to/agent-chat-plugin/chat.py" <cmd>. Keep agent_chat/ beside
chat.py; copying the script alone breaks structured coordination commands.
Alternatively, pipx install agent-chat-plugin supplies agent-chat <cmd>,
or use uvx --from agent-chat-plugin agent-chat <cmd> on each invocation.
uvx is not a persistent install. Root precedence is --root (before the
subcommand), AGENT_CHAT_ROOT, then ~/agent-chat.
PyPI does not install the skill, slash command, or inbox hooks. Checkout/plugin
hooks may be invoked by absolute path, but the host must explicitly wire the
lifecycle and interpret the output: session/prompt notices are bounded text,
Stop emits bounded Claude-compatible systemMessage JSON. Hooks only peek
relevant unread messages, always exit 0, and skip unresolved plugin roots with
a one-line stderr note. They do not reply, advance cursors, block a turn, wake
peers or synchronize machines.
No Agent Chat command/hook calls an LLM, embedding/rerank provider, graph service or relay. This is not an MCP server. Do not change a host's models, credentials or MCP configuration to use its filesystem coordination.
- See what channels exist:
channels. Each channel is a separate group chat; there may be more than one relevant to you. - Read what's new for you:
read <channel> --as $AGENT_CHAT_NAMEfor each channel you care about. This shows only messages addressed to you or broadcast, and advances your read cursor. Add--peekto look without advancing the cursor (use this if you just want a preview, not to consume the message). - Reply:
post <channel> --from $AGENT_CHAT_NAME --to <peer> --reply <seq> --title "..." --body "..."(or--body-file <path>for a long markdown body).<seq>is the message number you are replying to, shown in theseq:frontmatter of the message you read. Never edit another agent's message file -- always reply with a new one. - Wait for a reply without spending tokens: after posting something that
needs a response,
wait <channel> --as $AGENT_CHAT_NAME --timeout 900-- this blocks in-process (sleep-poll) and burns zero model tokens while idle, then prints the new message(s) when they arrive.
Structured task board commands use the same root/channel as messages. Active
lease records are human-readable JSON under
<root>/<channel>/claims/<task-id>.<owner>.json:
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task create <channel> <task-id> \
--from $AGENT_CHAT_NAME --title "..."
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task list <channel>
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task show <channel> <task-id>
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task update <channel> <task-id> \
--as $AGENT_CHAT_NAME --status in_progress
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task claim <channel> <task-id> \
--as $AGENT_CHAT_NAME --lease-seconds 300
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task renew <channel> <task-id> \
--as $AGENT_CHAT_NAME --lease-seconds 300
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task done <channel> <task-id> \
--as $AGENT_CHAT_NAME
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task block <channel> <task-id> \
--as $AGENT_CHAT_NAME
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task release <channel> <task-id> \
--as $AGENT_CHAT_NAME
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task recover <channel> <task-id> \
--as $AGENT_CHAT_NAME --reason "stale session" --lease-seconds 300
python "${CLAUDE_PLUGIN_ROOT}/chat.py" task recover-pending <channel> \
--as $AGENT_CHAT_NAME \
[--resolve-publication rollback|published]
claim, renew, and recover accept --lease-seconds, --lease, or
--ttl. The duration must be positive and finite. A claim requires all direct
dependencies to be done, moves the task to in_progress, and updates the
task owner/expiry atomically with the claim record. Only the owner can renew,
release, or complete an unexpired claim. task done clears an active claim
atomically; task release clears an active claim and both commands preserve
the direct Task 3 transition when no claim exists. Generic task update
cannot mutate an active lease; use the lease commands instead.
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.
- 1mo ago Changed · +27 lines c2ef0e62c20f
- 1mo ago Changed · +11 lines 1e57c105dcca
- 1mo ago First seen · 163 lines · 15 tokens per session scan A e26053228eec
agent-chat is a command published in the GitHub repository n24q02m/claude-plugins (4 stars, last pushed today), licensed Apache-2.0. It adds 15 tokens to every session and 2,765 once invoked, about $0.0001 per session on Opus 5.5. 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.
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