aiclilistener

Farm out AI tasks via Named Pipe to get isolated context. Use when processing large files, batch summarization, or to avoid context pollution. Each call runs in fresh context.

16 stars

Best use case

aiclilistener is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Farm out AI tasks via Named Pipe to get isolated context. Use when processing large files, batch summarization, or to avoid context pollution. Each call runs in fresh context.

Teams using aiclilistener 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

$curl -o ~/.claude/skills/aiclilistener/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/cli-automation/aiclilistener/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/aiclilistener/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How aiclilistener Compares

Feature / AgentaiclilistenerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Farm out AI tasks via Named Pipe to get isolated context. Use when processing large files, batch summarization, or to avoid context pollution. Each call runs in fresh context.

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

# AIclilistener Skill

Farm out work to a separate Codex instance running as a Named Pipe service. Each request gets **fresh, isolated context** - perfect for avoiding hallucinations when processing large amounts of data.

## When to Use This Skill

- **Large file processing**: Summarize files without filling your main context
- **Batch operations**: Process multiple files with isolated context per file
- **Context pollution prevention**: Keep your main conversation clean
- **Script automation**: Write scripts that leverage AI for specific tasks

## Prerequisites

1. AIclilistener service must be running:
   ```powershell
   cd path\to\AIclilistener\codex\windows
   .\Start-Service.bat
   ```

2. Ask the user: "Is the AIclilistener service running?"

## Usage Patterns

### Direct Call (Interactive)

Use CodexClient.ps1 to send a request and get a response:

```powershell
# Simple prompt
.\CodexClient.ps1 -Prompt "Summarize this: [content]"

# With options
.\CodexClient.ps1 -Prompt "Analyze this code" -Sandbox read-only -TimeoutSeconds 120
```

### Script Generation (Automation)

Generate PowerShell scripts that use AIclilistener:

```powershell
# Example: Summarize a file
$content = Get-Content -Path "C:\path\to\file.txt" -Raw
$prompt = "Summarize this file:`n$content"

# Call the service
$result = & ".\CodexClient.ps1" -Prompt $prompt -Raw

# Parse the result
$responses = $result | Where-Object { $_ -match '^\{' } | ForEach-Object { $_ | ConvertFrom-Json }
$finalResult = $responses | Where-Object { $_.status -eq 'success' }
$summary = $finalResult.result.message
```

### Batch File Processing

Use the built-in CSV processor with custom prompts:

```powershell
# Create CSV with file paths
@"
FilePath,Category
C:\docs\report.docx,Reports
C:\code\app.py,Code
"@ | Out-File files.csv

# Run with default summarization prompt (outputs files_processed.csv)
.\Process-Files.ps1 -CsvPath files.csv

# Run with custom prompt using placeholders
.\Process-Files.ps1 -CsvPath files.csv -Prompt "Extract all dates from: {fileContent}"

# Resume if interrupted
.\Process-Files.ps1 -CsvPath files.csv -Resume
```

Prompt placeholders: `{fileName}`, `{extension}`, `{filePath}`, `{fileContent}`

## Context Isolation

Each call to AIclilistener spawns a **fresh codex process**. This means:

- No memory of previous calls
- No context pollution between requests
- Clean slate for each task
- Ideal for processing many items independently

## JSON Request Format

```json
{
  "prompt": "Your task here",
  "options": {
    "sandbox": "read-only",
    "timeout_seconds": 120
  }
}
```

## JSON Response Format

```json
{
  "status": "success",
  "result": {
    "message": "The AI response...",
    "events": [...]
  },
  "duration_ms": 1234
}
```

## Service Commands

- `ping` - Health check
- `status` - Service info
- `shutdown` - Stop service

## Source Code

Optional: Get the latest version from GitHub:
```powershell
git clone https://github.com/WebSurfinMurf/AIclilistener.git
```

## Troubleshooting

- **"Pipe not found"**: Start the service with `.\Start-Service.bat`
- **Timeout errors**: Increase `-TimeoutSeconds` parameter
- **Service not responding**: Check the service window for errors

Related Skills

bgo

10
from diegosouzapw/awesome-omni-skill

Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.

Coding & Development

mcp-create-declarative-agent

16
from diegosouzapw/awesome-omni-skill

Skill converted from mcp-create-declarative-agent.prompt.md

MCP Architecture Expert

16
from diegosouzapw/awesome-omni-skill

Design and implement Model Context Protocol servers for standardized AI-to-data integration with resources, tools, prompts, and security best practices

mathem-shopping

16
from diegosouzapw/awesome-omni-skill

Automatiserar att logga in på Mathem.se, söka och lägga till varor från en lista eller recept, hantera ersättningar enligt policy och reservera leveranstid, men lämnar varukorgen redo för manuell checkout.

math-modeling

16
from diegosouzapw/awesome-omni-skill

本技能应在用户要求"数学建模"、"建模比赛"、"数模论文"、"数学建模竞赛"、"建模分析"、"建模求解"或提及数学建模相关任务时使用。适用于全国大学生数学建模竞赛(CUMCM)、美国大学生数学建模竞赛(MCM/ICM)等各类数学建模比赛。

matchms

16
from diegosouzapw/awesome-omni-skill

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

managing-traefik

16
from diegosouzapw/awesome-omni-skill

Manages Traefik reverse proxy for local development. Use when routing domains to local services, configuring CORS, checking service health, or debugging connectivity issues.

managing-skills

16
from diegosouzapw/awesome-omni-skill

Install, find, update, and manage agent skills. Use when the user wants to add a new skill, search for skills that do something, check if skills are up to date, or update existing skills. Triggers on: install skill, add skill, get skill, find skill, search skill, update skill, check skills, list skills.

manage-agents

16
from diegosouzapw/awesome-omni-skill

Create, modify, and manage Claude Code subagents with specialized expertise. Use when you need to "work with agents", "create an agent", "modify an agent", "set up a specialist", "I need an agent for [task]", or "agent to handle [domain]". Covers agent file format, YAML frontmatter, system prompts, tool restrictions, MCP integration, model selection, and testing.

maintainx-automation

16
from diegosouzapw/awesome-omni-skill

Automate Maintainx tasks via Rube MCP (Composio). Always search tools first for current schemas.

mailsoftly-automation

16
from diegosouzapw/awesome-omni-skill

Automate Mailsoftly tasks via Rube MCP (Composio). Always search tools first for current schemas.

mails-so-automation

16
from diegosouzapw/awesome-omni-skill

Automate Mails So tasks via Rube MCP (Composio). Always search tools first for current schemas.