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Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks disposition.

Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.

Confirma e envia todas as alterações locais para o repositório remoto.

Reviews Swift code for concurrency safety, error handling, memory management, and common mistakes. Use when reviewing .swift files for async/await patterns, actor isolation, Sendable conformance, or general Swift best practices.

Use when the user wants web research: gathering cited, multi-angle evidence on a specific question. Triggers on: \"research X for me\", \"do web research on\", \"look up sources for\", \"find citations for\", \"gather evidence on\", \"what does the web say about X\". Also invoked programmatically by other beagle skills (prfaq-beagle Ignition, brainstorm-beagle reference points, strategy-interview

Mandatory verification steps for all code reviews to reduce false positives. Load this skill before reporting ANY code review findings.

Reviews Phoenix LiveView code for lifecycle patterns, assigns/streams usage, components, and security. Use when reviewing LiveView modules, .heex templates, or LiveComponents.

Respond to review comments on a PR after evaluation and fixes

Analyze repo, detect stack, trace changes to user-facing entry points, generate E2E YAML test plan

Reviews Go test code for proper table-driven tests, assertions, and coverage patterns. Use when reviewing *_test.go files.

Reviews tokio async runtime usage for task management, sync primitives, channel patterns, and runtime configuration. Covers Rust 2024 edition changes including async fn in traits, RPIT lifetime capture, LazyLock, and if-let temporary scoping. Use when reviewing Rust code that uses tokio, async/await patterns, spawn, channels, or async synchronization. Also covers tokio-util, tower, and hyper integ

Applies fixes from a prior review-llm-artifacts run, with safe/risky classification. Respects verify-llm-artifacts output when present to skip false positives.