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Update README with correct agent count and model assignments

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- Update agent count from 71 to 75 to reflect current repository state
- Correct model assignment counts: Haiku (15), Sonnet (45), Opus (15)
- Add hr-pro to Sonnet model section and Business & Marketing guidance
- Fix model distribution after recent PR merges
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Seth Hobson
2025-08-15 22:34:11 -04:00
parent f0a6158807
commit 3b246deeb0
1 changed files with 7 additions and 5 deletions
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README.md
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@@ -35,7 +35,7 @@ A comprehensive collection of specialized AI subagents for [Claude Code](https:/
## Overview ## Overview
This repository contains 71 specialized subagents that extend Claude Code's capabilities. Each subagent is an expert in a specific domain, automatically invoked based on context or explicitly called when needed. All agents are configured with specific Claude models based on task complexity for optimal performance and cost-effectiveness. This repository contains 75 specialized subagents that extend Claude Code's capabilities. Each subagent is an expert in a specific domain, automatically invoked based on context or explicitly called when needed. All agents are configured with specific Claude models based on task complexity for optimal performance and cost-effectiveness.
## Available Subagents ## Available Subagents
@@ -131,9 +131,9 @@ This repository contains 71 specialized subagents that extend Claude Code's capa
## Model Assignments ## Model Assignments
All 71 subagents are configured with specific Claude models based on task complexity: All 75 subagents are configured with specific Claude models based on task complexity:
### 🚀 Haiku (Fast & Cost-Effective) - 16 agents ### 🚀 Haiku (Fast & Cost-Effective) - 15 agents
**Model:** `haiku` **Model:** `haiku`
- `data-scientist` - SQL queries and data analysis - `data-scientist` - SQL queries and data analysis
- `api-documenter` - OpenAPI/Swagger documentation - `api-documenter` - OpenAPI/Swagger documentation
@@ -152,7 +152,7 @@ All 71 subagents are configured with specific Claude models based on task comple
- `seo-cannibalization-detector` - Keyword overlap detection - `seo-cannibalization-detector` - Keyword overlap detection
- `seo-content-planner` - Content calendars and outlines - `seo-content-planner` - Content calendars and outlines
### ⚡ Sonnet (Balanced Performance) - 40 agents ### ⚡ Sonnet (Balanced Performance) - 45 agents
**Model:** `sonnet` **Model:** `sonnet`
**Development & Languages:** **Development & Languages:**
@@ -203,6 +203,7 @@ All 71 subagents are configured with specific Claude models based on task comple
- `seo-content-auditor` - Content quality and E-E-A-T analysis - `seo-content-auditor` - Content quality and E-E-A-T analysis
- `seo-authority-builder` - Authority signal optimization - `seo-authority-builder` - Authority signal optimization
- `seo-content-writer` - SEO-optimized content creation - `seo-content-writer` - SEO-optimized content creation
- `hr-pro` - HR operations and corporate policy enforcement
### 🧠 Opus (Maximum Capability) - 15 agents ### 🧠 Opus (Maximum Capability) - 15 agents
**Model:** `opus` **Model:** `opus`
@@ -451,6 +452,7 @@ payment-integration → security-auditor → Validated implementation
- **sales-automator**: Cold emails, follow-ups, proposals, lead nurturing - **sales-automator**: Cold emails, follow-ups, proposals, lead nurturing
- **customer-support**: Support tickets, FAQs, help documentation, troubleshooting - **customer-support**: Support tickets, FAQs, help documentation, troubleshooting
- **legal-advisor** - Draft privacy policies, terms of service, disclaimers, and legal notices - **legal-advisor** - Draft privacy policies, terms of service, disclaimers, and legal notices
- **hr-pro** - HR operations, policy enforcement, and corporate compliance
## Best Practices ## Best Practices