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/agent-one-lab/agentfly/indexgit clone --depth 1 https://github.com/Agent-One-Lab/AgentFlyWhat 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 | $0.00300 |
| Opus 5 | $0.00000 | $0.00150 |
| Sonnet 5 | $0.00000 | $0.00060 |
| Haiku 4.5 | $0.00000 | $0.00030 |
Grade A, and why
index 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 2d 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.
What it actually says
Agents API Reference
Overview
AgentFly provides a comprehensive agent system with a base class and specialized implementations for different use cases. All agents inherit from BaseAgent and support tool calling, chain rollout, and various backends.
Structure
- Agent - Base agent class and implementations
- LLM Backends - Language model backends
- Rollout - Agent rollout strategies
Usage Examples
Basic Agent Creation
from agentfly.agents import ReactAgent
from agentfly.tools import get_tools_from_names
# Create a ReactAgent with tools
agent = ReactAgent(
model_name_or_path="gpt2",
tools=get_tools_from_names(["calculator", "google_search"]),
template="react"
)
Using AutoAgent
from agentfly.agents import AutoAgent
# Create agent from config
config = {
"agent_type": "react",
"model_name_or_path": "gpt2",
"template": "react",
"tools": ["calculator"]
}
agent = AutoAgent.from_config(config)
Custom Agent
from agentfly.agents import BaseAgent
class CustomAgent(BaseAgent):
def parse(self, response):
# Custom parsing logic
pass
def generate(self, messages):
# Custom generation logic
pass
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.
- 2d ago First seen · 58 lines · 0 tokens per session scan A efb79e0063a8
index is an agent published in the GitHub repository Agent-One-Lab/AgentFly (122 stars, last pushed 6d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 300 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.
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