Prepare a regression investigation by fixing the exact before and after source versions, preserving PR or commit context, and producing a sealed preparation record that explains change boundaries and evidence collection limits.
中文简介正在准备中。当前显示英语简介。
Use when pinning before/after sources and collecting PR or commit context for a regression investigation.
安装前可以查看交给 AI 代理的指令内容。
Input: PR URL or repository plus commit/range, and registry assignment. Follow project guidance after resolving the target commit.
The same inputs have a verified preparation record; reuse it.
uv run --no-project with
repository, S0, S1 and a new directory, or equivalent Git commands for special
source needs. Preserve dependency/submodule/LFS revisions. Exclude later history;
keep exports pristine and build in separate copies.prepare.json with boundary explanations, frozen context and
source artifacts. If blocked, preserve collected evidence and name the prerequisite.Keep detailed evidence in the sealed package. Return only:
complete or blocked, matching the record.prepare.json path, or why none was produced.还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问，或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
Build and test code with AddressSanitizer, a tool that detects invalid memory access during execution. Configure checks for C/C++ and unsafe Rust, investigate crash reports, and adjust settings for fuzzing, or testing with generated inputs.
中文简介正在准备中。当前显示英语简介。
Assess source code and live reproduction evidence to decide whether a change introduced a regression, a newly caused defect. Record supported conclusions, exclusions, severity, and unresolved gaps in an evidence-linked decision file.
中文简介正在准备中。当前显示英语简介。
Sets up AFL++ to test C/C++ programs with varied generated inputs, a technique called fuzzing. Covers running tests across CPU cores, monitoring progress, reducing input collections, and reproducing crashes for investigation.
中文简介正在准备中。当前显示英语简介。
Audits GitHub Actions workflows that run AI coding agents. Traces how attacker-controlled content reaches prompts, checks permissions and sandbox settings, and reports evidence, severity, and fixes for prompt injection and related configuration risks.
中文简介正在准备中。当前显示英语简介。
Reviews Algorand smart contracts written in TEAL or PyTeal for 11 vulnerability patterns. Produces a complete coverage table and findings with code references, severity ratings, and suggested fixes, with optional automated checks using Tealer.
中文简介正在准备中。当前显示英语简介。
Set up Atheris to test Python code and C extensions with automatically varied inputs. It guides test harness creation, coverage tracking to explore more code, and AddressSanitizer setup for finding memory errors.
中文简介正在准备中。当前显示英语简介。