Claude-skill-registry 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.
git clone https://github.com/majiayu000/claude-skill-registry
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/aiclilistener" ~/.claude/skills/majiayu000-claude-skill-registry-aiclilistener && rm -rf "$T"
skills/data/aiclilistener/SKILL.mdAIclilistener 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
-
AIclilistener service must be running:
cd path\to\AIclilistener\codex\windows .\Start-Service.bat -
Ask the user: "Is the AIclilistener service running?"
Usage Patterns
Direct Call (Interactive)
Use CodexClient.ps1 to send a request and get a response:
# 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:
# 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:
# 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
{ "prompt": "Your task here", "options": { "sandbox": "read-only", "timeout_seconds": 120 } }
JSON Response Format
{ "status": "success", "result": { "message": "The AI response...", "events": [...] }, "duration_ms": 1234 }
Service Commands
- Health checkping
- Service infostatus
- Stop serviceshutdown
Source Code
Optional: Get the latest version from GitHub:
git clone https://github.com/WebSurfinMurf/AIclilistener.git
Troubleshooting
- "Pipe not found": Start the service with
.\Start-Service.bat - Timeout errors: Increase
parameter-TimeoutSeconds - Service not responding: Check the service window for errors