counselors

Fans out code review prompts to multiple AI agents and synthesizes their responses via the counselors npm package.

1|Updated Feb 6, 2026

Search Tags:#code review #parallel processing #security analysis #multi-agent #AI collaboration #feedback synthesis

Ready to run

npx skills add https://github.com/skinnyandbald/fish-skills --skill counselors

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: counselors
Source: https://github.com/skinnyandbald/fish-skills/tree/main/skills/counselors
Command: npx skills add https://github.com/skinnyandbald/fish-skills --skill counselors

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines code reviews by distributing a prompt across multiple AI agents simultaneously, then synthesizing their diverse feedback into a single, actionable report.

Core Features & Use Cases

Parallel Agent Execution: Leverages multiple AI models for comprehensive analysis.
Contextual Awareness: Gathers relevant code, git history, and file references.
Synthesized Feedback: Consolidates opinions, disagreements, risks, and recommendations.
Use Case: Submit a complex code change for review, and have several specialized AI agents provide security, performance, and style feedback, all compiled into one summary.

Quick Start

Use the counselors skill to review the authentication flow for security issues.

Frequently Asked Questions about counselors

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I run a multi-agent AI code review to get diverse perspectives on code quality?▼

Multi-agent AI code review distributes your prompt across several AI agents simultaneously to analyze code quality, security, and correctness. The agents execute in parallel, and their responses are synthesized into a single actionable feedback report.

What is parallel processing for AI collaboration and when do I need it for security analysis?▼

Parallel processing for AI collaboration fans out prompts to multiple AI agents at once. You need it when analyzing complex code changes for security vulnerabilities or performance issues, requiring diverse specialized perspectives synthesized into one summary.

How do I synthesize feedback from multiple AI agents reviewing my code?▼

To synthesize feedback from multiple AI agents, the system orchestrates parallel responses and consolidates opinions, disagreements, risks, and recommendations. This feedback synthesis compiles diverse agent outputs into a unified, actionable report.

Do I need the counselors npm package to orchestrate multiple AI agents for code review?▼

Yes, you need the counselors npm package to facilitate agent orchestration and response aggregation. This dependency manages the parallel execution of multiple AI agents and synthesizes their diverse code review feedback.

Can I use multi-agent code review to analyze git history and file references for security issues?▼

Yes, multi-agent code review gathers relevant code, git history, and file references to provide contextual awareness. Multiple specialized AI agents analyze this context to deliver comprehensive security, performance, and style feedback.

What are the limitations of using parallel AI agents for code review?▼

Limitations of parallel AI code review include the dependency on the counselors npm package for agent orchestration. Complex code changes require sufficient contextual data from git history and file references to generate accurate synthesized feedback.