experimental-code-coverage-cq-debugger
Executes the phased, multi-skill code coverage debugging playbook for triaging underreported code coverage in the Gerrit Commit Queue (CQ).
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Executes the phased, multi-skill code coverage debugging playbook for triaging underreported code coverage in the Gerrit Commit Queue (CQ).
Verifies and initializes the Chromium development environment and dependencies required for running code coverage tools and services.
Triages Chrome code coverage bugs, initializes the environment, and delegates to the appropriate debugging sub-agent (CQ or CI) using a shared state file.
Validates code coverage Swarming execution logs, CAS input/output profile artifacts, and profile generation environments to isolate remote trybot code coverage failures.
Prepares a Gerrit CL for code coverage verification try jobs. Adds dummy comments to trigger builds, optimizes builder configs by isolating test suites, and commits all changes.
Retrieves and analyzes Chromium per-CL code coverage data from the Findit API. Records per-CL coverage metrics for all modified source files and extracts unexecuted code lines.
Finds the executable test suites (e.g., `browser_tests`, `unit_tests`) responsible for compiling and executing a specific target source code file or test file in Chromium on Linux.
Diagnose Chromium GN dependency and include-visibility failures, including BUILD.gn deps/public_deps, DEPS include rules, private headers, and circular dependencies. Use for build or gn check dependency errors, not C++/link/runtime/test failures.
Identify and safely remove expired Chromium histograms (dead metrics/technical debt). Use this skill when a contributor asks to clean up metrics, fix code health issues related to histograms, remove obsolete code, or work on a histogram cleanup task.
Iteratively investigate the source of latency in a Chrome build or in an experiment. Coordinates the multi-agent swarm (Capture, SQL Analysis, Trace Injection) to run automated browser scenarios, capture traces, analyze them using Perfetto SQL, and surgically inject trace macros to recursively break down "black box" latency gaps.