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.
npx agentmods add agents/wiseaidotdev/autogpt/overviewgit clone --depth 1 https://github.com/wiseaidotdev/autogptWhat 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 | $0.00000 | $0.00924 |
| Opus 5 | $0.00000 | $0.00462 |
| Sonnet 5 | $0.00000 | $0.00185 |
| Haiku 4.5 | $0.00000 | $0.00092 |
Grade A, and why
overview 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 yesterday.
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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Built-in Agents Overview
AutoGPT 0.2 ships with 9 built-in autonomous agents, each specializing in a different domain. They are independently usable via CLI subcommands and composable via the SDK's agents! macro.
Agent Roster
| Agent | Feature Flag | CLI Subcommand | Role |
|---|---|---|---|
GenericGPT |
cli |
(default, no subcommand) | Autonomous software engineering: reasons, edits files, builds, learns |
ManagerGPT |
gpt |
autogpt man |
Task orchestration across all agents |
ArchitectGPT |
gpt |
autogpt arch |
System architecture diagram generation |
BackendGPT |
gpt |
autogpt back |
Backend source code generation |
FrontendGPT |
gpt |
autogpt front |
Frontend UI code generation |
DesignerGPT |
img |
autogpt design |
AI image and UI mockup generation |
GitGPT |
git |
(automatic) | Atomic Git commits from agent output |
MailerGPT |
mail |
(SDK only) | Email reading and automated sending |
OptimizerGPT |
gpt |
(SDK only) | Codebase modularization and refactoring |
Agent Architecture
Every agent in AutoGPT is built from three composable layers:
┌─────────────────────────────────────────┐
│ Agent Struct │
│ (e.g. ArchitectGPT, BackendGPT, etc.) │
├─────────────────────────────────────────┤
│ AgentGPT Core │
│ persona · behavior · memory · status │
│ tools · knowledge · planner · context │
├─────────────────────────────────────────┤
│ ClientType (LLM Client) │
│ Gemini · OpenAI · Claude · XAI · Co │
└─────────────────────────────────────────┘
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.
- yesterday First seen · 98 lines · 0 tokens per session scan A e0062aedcdb1
overview is an agent published in the GitHub repository wiseaidotdev/autogpt (115 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 924 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
agent_class
The Agent class is the core orchestrator in AgentForge. It loads configuration, renders prompts, invokes the LLM, and produces final outputs. Agents can be subclassed for custom logic.
agent_prompts
AgentForge uses YAML-based prompt templates to drive agent behaviors. All prompt files live under.
custom_agents
This is an advanced extension reference.
agents
Agents are the orchestrators in AgentForge, binding configuration, prompts, models, and storage into end-to-end AI workflows. An agent.
verify
Verifies edits conform to project AGENTS.md and suggests simplifications.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.