Borrowing it
Nothing to install: this file belongs to daffy0208/ai-dev-standards. 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/daffy0208/ai-dev-standards/main/.claude/agents/agent-types.mdgit clone --depth 1 https://github.com/daffy0208/ai-dev-standardsWrote 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/agents/daffy0208/ai-dev-standards/agent-types)<a href="https://agentmods.dev/agents/daffy0208/ai-dev-standards/agent-types"><img src="https://agentmods.dev/badge/agents/daffy0208/ai-dev-standards/agent-types/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/agents/daffy0208/ai-dev-standards/agent-types"><img src="https://agentmods.dev/badge/agents/daffy0208/ai-dev-standards/agent-types.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 | $0.00000 | $0.03597 |
| Opus 5.5 | $0.00000 | $0.01439 |
| Sonnet 5.5 | $0.00000 | $0.00719 |
| Haiku 4.5 | $0.00000 | $0.00360 |
Grade A, and why
agent-types 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 1mo 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 — 711 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Types: Complete Taxonomy
Comprehensive classification of all agent types available in Claude Code and the ai-dev-standards repository.
Overview
Total Agent Types: 10
- 4 Claude Code Built-in Agents - Native CLI agents
- 6 Skill-Based Agents - Skills that function as autonomous agents
1. Claude Code Built-in Agents (4)
1.1 General-Purpose Agent
Type: Default, Multi-Purpose Status: Active Invocation: Default mode
Purpose: Comprehensive development agent for most tasks including code search, analysis, editing, and multi-step research.
Core Capabilities:
- Multi-file analysis and editing
- Complex codebase exploration
- System architecture understanding
- Multi-step research tasks
- File operations (read, write, edit)
- Pattern recognition and matching
Best For:
- Bug investigation and fixes
- Feature implementation
- Refactoring
- Code review preparation
- Ongoing development work
Performance:
- Speed: Variable (depends on task)
- Depth: High
- Memory: Handles large files efficiently
Integration:
- Can invoke any of 59 skills
- Access to 36 MCP servers
- Works with all tools and components
Documentation: general-purpose.md
1.2 Explore Agent
Type: Codebase Discovery Status: Active Invocation: Via explore mode
Purpose: Fast, configurable codebase exploration with three thoroughness levels.
Modes:
- Quick - Fast overview (seconds to minutes)
- Medium - Balanced exploration (5-15 minutes) [Default]
- Very Thorough - Deep analysis (30+ minutes)
Core Capabilities:
- Initial repository assessment
- Architecture understanding
- Pattern discovery
- Rapid familiarization
- Dependency mapping
Best For:
- New codebase onboarding
- Pre-refactoring analysis
- Security audit preparation
- Architecture documentation
- Migration planning
Performance:
- Speed: Configurable (Quick/Medium/Very Thorough)
- Depth: Configurable by mode
- Memory: Scales with thoroughness level
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.
- 1mo ago First seen · 711 lines · 0 tokens per session scan A c87346e45f75
agent-types is an agent published in the GitHub repository daffy0208/ai-dev-standards (38 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,597 tokens. 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 2026-08-30.
Other agents, from other repositories
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.