Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote 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/proffesor-for-testing/agentic-qe/agent-types)<a href="https://agentmods.dev/agents/proffesor-for-testing/agentic-qe/agent-types"><img src="https://agentmods.dev/badge/agents/proffesor-for-testing/agentic-qe/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/proffesor-for-testing/agentic-qe/agent-types"><img src="https://agentmods.dev/badge/agents/proffesor-for-testing/agentic-qe/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 | $0.00017 | $0.01871 |
| Opus 5.5 | $0.00007 | $0.00748 |
| Sonnet 5.5 | $0.00003 | $0.00374 |
| Haiku 4.5 | $0.00002 | $0.00187 |
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 9d 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.
This is a copy
100% identical to agent-types — 228 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Types Reference
Complete guide to all 87 available agent types in Claude Flow V3.
Core Development (5)
| Agent | Description | Best For |
|---|---|---|
coder |
Code implementation with neural patterns | Feature development, bug fixes |
reviewer |
Code quality assurance | PR reviews, security checks |
tester |
Testing with automation | Unit tests, integration tests |
planner |
Strategic task planning | Project planning, roadmaps |
researcher |
Information gathering | Requirements, documentation |
V3 Specialized (12)
| Agent | Description | Best For |
|---|---|---|
security-architect |
Security architecture | Threat modeling, design |
security-auditor |
CVE remediation | Vulnerability scanning |
memory-specialist |
AgentDB unification | 150x-12,500x search |
performance-engineer |
Optimization targets | 2.49x-7.47x speedup |
core-architect |
DDD restructure | Domain modeling |
adr-architect |
Architecture decisions | ADR documentation |
claims-authorizer |
Access control | Claims-based auth |
ddd-domain-expert |
Domain design | Bounded contexts |
reasoningbank-learner |
Pattern learning | Self-improvement |
sona-learning-optimizer |
Neural optimization | SONA adaptation |
sparc-orchestrator |
SPARC methodology | Development workflow |
v3-integration-architect |
V3 integration | System integration |
Swarm Coordination (6)
| Agent | Description | Best For |
|---|---|---|
hierarchical-coordinator |
Queen-led coordination | Complex projects |
mesh-coordinator |
P2P peer networks | Research tasks |
adaptive-coordinator |
Dynamic topology | Unknown workloads |
collective-intelligence-coordinator |
Consensus decisions | Group decisions |
swarm-memory-manager |
Distributed memory | Data sharing |
coordinator-swarm-init |
Swarm initialization | Setup |
Consensus Agents (7)
| Agent | Description | Best For |
|---|---|---|
byzantine-coordinator |
BFT consensus | Fault tolerance |
raft-manager |
Leader-based consensus | Consistent state |
gossip-coordinator |
Eventual consistency | Scalability |
crdt-synchronizer |
CRDT replication | Conflict-free sync |
quorum-manager |
Quorum consensus | Voting systems |
security-manager |
Consensus security | Secure coordination |
consensus-coordinator |
General consensus | Distributed systems |
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.
- 9d ago Changed · +190 lines · +17 tokens per session 606b2a455e99
- 1mo ago First seen · 27 lines · 0 tokens per session scan A d791bef16a13
agent-types is an agent published in the GitHub repository proffesor-for-testing/agentic-qe (506 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 1,871 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to agent-types, differing in 228 lines, and is treated as a copy.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
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.
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.
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.