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Python Atheris Fuzzer

trailofbits/skills

Atheris is a coverage-guided Python fuzzer built on libFuzzer for fuzzing pure Python code and C extensions, with AddressSanitizer support to catch memory corruption and an easy harness setup for command-line fuzz runs.

Python Atheris Fuzzer

trailofbits/skills

Atheris is a coverage-guided Python fuzzer built on libFuzzer for fuzzing pure Python code and C extensions, with AddressSanitizer support to catch memory corruption and an easy harness setup for command-line fuzz runs.

Cargo Fuzz Guide

trailofbits/skills

cargo-fuzz provides a Cargo subcommand that lets Rust projects fuzz with libFuzzer, automating sanitizer flags, corpus/dictionary handling, crash replay, coverage reports, and harness rules, so teams can quickly validate unsafe-aware code.

Fuzzing Coverage Analysis

coverage-analysis

trailofbits/skills

Analyzes code coverage during fuzzing campaigns to assess harness quality, spot blockers like magic values, and guide instrumentation or corpus updates.

Claude Eval Harness

affaan-m/everything-claude-code

Formal evaluation framework for Claude Code sessions that applies evaluation-driven development to define capability and regression checks, run deterministic and model graders, and track pass@k/pass^k reliability metrics before shipping.

LLM Evaluation Harness

evaluating-llms-harness

Orchestra-Research/AI-Research-SKILLs

Evaluates large language models across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag) with standardized prompts and metrics, making it easy to benchmark HuggingFace or API models, compare releases, and track training progress.

Fuzzing Harness Writing

harness-writing

trailofbits/skills

Guides developers in crafting and refining fuzzing harnesses that parse random fuzzer input, validate data, and exercise targeted API paths to improve coverage and find reproducible bugs.

LibFuzzer Coverage Fuzzing

trailofbits/skills

LibFuzzer is LLVM’s in-process coverage-guided fuzzer for C/C++ projects compiled with Clang, providing a quick harness-based setup that can later transition to more advanced fuzzers while maintaining reproducible, high-throughput testing.

NeMo LLM Evaluator

nemo-evaluator-sdk

Orchestra-Research/AI-Research-SKILLs

Enterprise NeMo Evaluator SDK runs over 100 benchmarks from 18+ harnesses with multi-backend execution (Docker, Slurm, cloud) to give reproducible, scalable LLM evaluation workflows.

OSS-Fuzz Continuous Fuzzing

trailofbits/skills

OSS-Fuzz gives open-source teams free distributed infrastructure for continuous fuzz testing, letting you build Docker images, compile sanitizing fuzzers, run harnesses, and review coverage/bugs through the helper.py CLI instead of hosting your own servers.

Ruby Fuzzer Guide

trailofbits/skills

Ruzzy is a coverage-guided Ruby fuzzer leveraging libFuzzer to exercise both pure Ruby code and native C extensions; follow the provided installer, harness patterns, and sanitizer-aware runs to validate Ruby apps or gems for memory safety issues.

Designing Robust AI Agent Systems

agent-harness-construction

affaan-m/everything-claude-code

This comprehensive guide outlines best practices for building reliable and robust AI agent harnesses. It covers optimizing action spaces, defining structured tools, managing observation formats, and implementing essential error recovery contracts. Use these principles to dramatically improve agent completion rates, manage context budgets effectively, and transition AI prototypes into stable, production-grade autonomous systems.

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