Borrowing it
Nothing to install: this file belongs to cacr92/WeReply. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cacr92/WeReply/main/.claude/skills/ipc-communication/SKILL.mdgit clone --depth 1 https://github.com/cacr92/WeReplyWrote 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/skills/cacr92/wereply/ipc-communication)<a href="https://agentmods.dev/skills/cacr92/wereply/ipc-communication"><img src="https://agentmods.dev/badge/skills/cacr92/wereply/ipc-communication/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/skills/cacr92/wereply/ipc-communication"><img src="https://agentmods.dev/badge/skills/cacr92/wereply/ipc-communication.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 | $0.00107 | $0.04243 |
| Opus 5 | $0.00053 | $0.02122 |
| Sonnet 5 | $0.00021 | $0.00849 |
| Haiku 4.5 | $0.00011 | $0.00424 |
Grade A, and why
ipc-communication 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 8d 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 — 707 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IPC Communication Skill
Expert guidance for implementing Inter-Process Communication between Rust Orchestrator and Platform Agents using JSON protocol via stdin/stdout.
Overview
WeReply uses JSON-based IPC protocol for communication:
- Protocol: JSON messages via stdin/stdout
- Direction: Bidirectional (Orchestrator ↔ Agent)
- Message Format: Line-delimited JSON (one message per line)
- Character Encoding: UTF-8
Message Protocol Design
Message Types
use serde::{Deserialize, Serialize};
use specta::Type;
// Agent → Orchestrator 消息
#[derive(Serialize, Deserialize, Type, Debug)]
#[serde(tag = "type")]
pub enum AgentMessage {
MessageNew {
content: String,
sender: String,
timestamp: String,
},
CommandResponse {
success: bool,
#[serde(skip_serializing_if = "Option::is_none")]
error: Option<String>,
},
HealthStatus {
status: String, // "ok", "degraded", "error"
agent_type: String, // "windows_wxauto", "macos_accessibility"
},
Heartbeat {
timestamp: f64,
},
Error {
message: String,
#[serde(skip_serializing_if = "Option::is_none")]
code: Option<String>,
},
}
// Orchestrator → Agent 消息
#[derive(Serialize, Deserialize, Type, Debug)]
#[serde(tag = "type")]
pub enum OrchestratorCommand {
WriteInput {
content: String,
},
ClearInput,
HealthCheck,
Stop,
}
Message Format Examples
// Agent → Orchestrator: 新消息
{
"type": "MessageNew",
"content": "你好,最近怎么样?",
"sender": "张三",
"timestamp": "2024-01-23T10:30:00"
}
// Orchestrator → Agent: 写入输入框
{
"type": "WriteInput",
"content": "很好,谢谢!"
}
// Agent → Orchestrator: 命令响应
{
"type": "CommandResponse",
"success": true
}
// Agent → Orchestrator: 错误
{
"type": "Error",
"message": "无法访问微信窗口",
"code": "ACCESS_DENIED"
}
Rust Orchestrator Implementation
Agent Process Manager
use tokio::process::{Child, Command};
use tokio::io::{AsyncBufReadExt, AsyncWriteExt, BufReader};
use std::process::Stdio;
pub struct AgentProcess {
child: Child,
stdin: tokio::process::ChildStdin,
stdout_reader: BufReader<tokio::process::ChildStdout>,
}
impl AgentProcess {
pub async fn spawn(agent_path: &str) -> anyhow::Result<Self> {
let mut child = Command::new(agent_path)
.stdin(Stdio::piped())
.stdout(Stdio::piped())
.stderr(Stdio::piped())
.spawn()?;
let stdin = child.stdin.take()
.ok_or_else(|| anyhow!("无法获取 Agent stdin"))?;
let stdout = child.stdout.take()
.ok_or_else(|| anyhow!("无法获取 Agent stdout"))?;
let stdout_reader = BufReader::new(stdout);
Ok(Self {
child,
stdin,
stdout_reader,
})
}
pub async fn send_command(&mut self, command: OrchestratorCommand) -> anyhow::Result<()> {
let json = serde_json::to_string(&command)?;
self.stdin.write_all(json.as_bytes()).await?;
self.stdin.write_all(b"\n").await?;
self.stdin.flush().await?;
Ok(())
}
pub async fn read_message(&mut self) -> anyhow::Result<AgentMessage> {
let mut line = String::new();
self.stdout_reader.read_line(&mut line).await?;
if line.is_empty() {
return Err(anyhow!("Agent 已关闭输出"));
}
let message = serde_json::from_str(&line)?;
Ok(message)
}
pub async fn kill(&mut self) -> anyhow::Result<()> {
self.child.kill().await?;
Ok(())
}
}
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 707 lines · 107 tokens per session scan A 03898405c735
ipc-communication is a skill published in the GitHub repository cacr92/WeReply (6 stars, last pushed 7mo ago), licensed MIT. It adds 107 tokens to every session and 4,243 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.
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