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Adversarial scenario generation and testing for coding agents

Project description

AgentFuzzer

License: MIT Python 3.10+ Tests

Adversarial scenario generation and testing for coding agents.

Quick Start

Quick Install

pip install agent-fuzzer
# Run fuzzing tests
agentfuzzer fuzz --model gpt-4 --count 20 --difficulty hard

# View report
agentfuzzer report -r fuzz_report.json

Scenario Categories

  • broken_code: Code with bugs the agent must fix
  • failing_tests: Tests that fail and need fixing
  • missing_deps: Missing or conflicting dependencies
  • network_errors: Network-related failures

License

MIT

Ecosystem

Part of the FableForge ecosystem — 21 open-source projects built from 210K real agent traces:

Project Description
Anvil Self-verified coding agent
VerifyLoop Plan→Execute→Verify→Recover framework
ErrorRecovery Self-healing middleware (3,725 error patterns)
FableForge-14B The fine-tuned 14B model (4-stage training)
ShellWhisperer 1.5B edge agent (phone/RPi, 50ms)
ReasonCritic Verification model (130 benchmark tasks)
TraceCompiler Compile traces → LoRA skills
AgentRuntime Persistent agent daemon (systemd for AI)
AgentSwarm Multi-agent from real trace transitions
AgentTelemetry Datadog for agents (token tracking, costs)
BenchAgent HumanEval for tool-use (107 tasks)
AgentDev VSCode extension with verification
TraceViz Trace replay visualizer (Next.js)
AgentSkills npm for agent behaviors
AgentCurriculum 5-stage progressive training
AgentFuzzer Adversarial testing for agents
AgentConstitution Safety guardrails from traces
CostOptimizer Token cost reduction (50-80%)
AgentProfiler Behavioral fingerprinting
TrajectoryDistiller Trace→training data pipeline
Fable5-Dataset HuggingFace dataset release

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