Results for “code-review”

Write, review, debug, test, or optimize Python code using the rustworkx graph library, with explicit handling of graph kind, index lifecycle, payload semantics, and algorithm result mapping.

Agent profile for inspect screenshots, viewports, layout overlaps, visual regressions, spacing, typography, and interaction states. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for design data pipelines, transformations, imports, exports, warehouse models, validation, and freshness checks. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for design motion systems, transitions, easing, reduced-motion behavior, and performance-safe animation. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for lead framework, dependency, database, SDK, and architecture migrations with sequencing and rollback. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for evaluate RAG quality, chunking, retrieval, citations, hallucination risks, freshness, and regression sets. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for handle CI/CD, environments, build pipelines, deployment topology, secrets, and operational readiness. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for prioritize product scope, user outcomes, MVP slices, roadmap tradeoffs, and launch criteria. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

P7 Senior Engineer mode — solution-driven execution under P8 supervision. Use when user says 'P7模式', '方案驱动', or when spawned as sub-task executor by P8. Produces: implementation plan + code + 3-question self-review, delivered via [P7-COMPLETION].

Drive Graphify from its CLI to build, refresh, query, export, and serve a durable code/corpus knowledge graph. Use when the user wants `.graphify/GRAPH_REPORT.md`, `graph.json`, `graph.html`, `graphify update`/`summary`/`query`/`path`/`explain`/`tree`, change-aware review context, git-hook or watch-based refresh, a stdio MCP graph server, or an install into jeo, jeopi, gjc, opencode, Claude, Codex, or Gemini. Also covers the honest structural fallback when native extraction is empty or misleading. Route simple locate/reference work to `codebase-search`, narrative knowledge-base work to `llm-wiki`, and project-memory handoff to `opencontext`. Triggers on: graphify, graphify update, graphify query, knowledge graph CLI, GRAPH_REPORT.md, graph.json, codebase graph, graph refresh, graphify install, graphify serve, review context, affected flows.

Enforces output quality, intellectual honesty, and continuous improvement across security analysis agents with anti-rationalization guards, self-critique loops, retry protocols, and quality gates.

Builds and reviews Apex code that constructs SOQL/SOSL at runtime, inspects schema metadata, and accesses fields dynamically, with guidance on injection prevention and FLS enforcement.

P7 Senior Engineer mode — solution-driven execution under P8 supervision. Use when user says 'P7模式', '方案驱动', or when spawned as sub-task executor by P8. Produces: implementation plan + code + 3-question self-review, delivered via [P7-COMPLETION].

Agent profile for plan PPC account structure, creative testing, budget hypotheses, measurement, and landing-page alignment. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for design test strategy across unit, integration, contract, E2E, visual, performance, and regression layers. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for write developer docs, user docs, API docs, tutorials, changelogs, and concise implementation notes. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.

Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. Iteratively fixes issues in source code, committing each fix atomically and re-verifying with before/after screenshots. For plan-mode design review (before implementation), use /plan-design-review. Use when asked to "audit the design", "visual QA", "check if it looks good", or "design polish". Proactively suggest when the user mentions visual inconsistencies or wants to polish the look of a live site. (gstack)

Learn Git workflow patterns including branching strategies, commit conventions, merge vs rebase, conflict resolution, and collaborative development best practices for teams of all sizes.

Update Azure Verified Modules (AVM) to their latest versions in Bicep files, with support for non-breaking changes and manual review for breaking changes.

Review and fix Swift Concurrency issues in Swift 6.2+ codebases by applying actor isolation, Sendable safety, and modern concurrency patterns with minimal behavior changes.

Use for writing, reviewing, debugging, testing, or validating Python mpmath arbitrary-precision numerical code. Trigger on mpf, mpc, mp.dps, workdps, interval arithmetic, high-precision quadrature, root finding, special functions, matrices, inverse transforms, or precision/convergence failures. Do not use for ordinary NumPy vectorization, SymPy symbolic manipulation, decimal currency arithmetic, or machine-float code with no precision requirement.

Produce a plain-language manual test plan from the context supplied to it — an executive summary, a high-level list of named tests, and a detail section per test with the steps a person follows by hand and the outcomes they should expect. Use when you want to create, draft, generate, or outline a manual test plan, manual QA steps, hands-on verification steps, or an acceptance walkthrough for a feature, change, branch, plan, or PR. When the plan holds more than five tests and at least two natural categories emerge, both the test list and the detail sections are organized under plain-language categories. When nothing in the supplied context can be manually tested, it says so and asks for more context instead of producing a document. Does not analyze code for automated test coverage gaps — use automated-test-planning. Does not write test code — use tdd. Does not review code quality — use code-review. Does not stress-test an existing plan — use iterative-plan-review.

Audit a repository, vet and prioritize evidence-backed findings, write drift-aware implementation plans, delegate bounded work, and independently verify results. Use when asked to improve, audit, modernize, harden, review, plan fixes for, or systematically reduce risk in a codebase. Use native isolated agents for implementation; use OpenRouter/free only for narrow advisory audit slices under its safety limits.

Audits natural-language programming artifacts such as SKILL.md, AGENTS.md, CLAUDE.md, slash commands, plugin manifests, hooks, rules, and prompt files. Use when reviewing AI-agent repositories, checking manifest-vs-disk consistency, scoring skill or agent quality, adding NL artifact CI gates, or diagnosing vocabulary and version drift across Claude Code, Codex, Cursor, Gemini, and Antigravity-style projects.

Orchestrate autonomous AI development pipelines through your Kanban board, managing multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions, covering ownership patterns, lifetimes, trait hierarchies, async/await with tokio, and error handling with Result/Option.

Provides a security checklist and code patterns for authentication, input validation, secrets management, SQL injection prevention, XSS, CSRF, rate limiting, and sensitive data handling.

Explains MariaDB Connector/C's `mysql_`-prefixed API, connection setup, result handling, prepared statements, and transaction behavior for writing or reviewing C code that talks to MariaDB.

Write, review, debug, or test Python datetime, date, timedelta, timezone, and zoneinfo code, especially UTC conversion, DST gaps and folds, recurring local schedules, parsing, and interval boundaries.

Agent profile for design AI/ML features, retrieval, model calls, structured outputs, cost controls, evals, and fallbacks. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for design and implement backend services, API logic, data access, jobs, auth boundaries, and error handling. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Agent profile for coordinate mobile app architecture across iOS, Android, Expo/React Native, offline states, permissions, and releases. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Enforces an algorithm-first discipline: state Big-O, data structure, and algorithm family before writing loops, queries, or recursion to catch O(n²), N+1, and brute-force defaults.

Audits AGENTS.md and CLAUDE.md files for bloat, redundancy, and ineffective rules, then runs A/B evals to prove which instructions are dead weight.

Design UI/UX in a Sage project — Figma to Blade, design tokens to Tailwind v4, Paper/Figma MCP integration, component design, layout design, responsive design, design-to-code workflow, visual design review, design system alignment, design approval before implementation