Results for “writing-review”

Explains MariaDB Connector/J JDBC driver behavior: auto-registration, URL schemes, prepared statement handling, batch inserts, transactions, fetch sizes, pooling, and failover. Use when writing or reviewing Java code that talks to MariaDB with the mariadb-java-client driver.

Use when writing or reviewing tests, or when asked how to write a good single test. Encodes the per-test rules behind the "test the contract / responsibility, not the implementation" principle — name and structure one behavior per `it`, drive through the public surface, stub only true external boundaries, control time and config via documented knobs, and keep tests clear, isolated, and refactor-resilient. The same rules drive both authoring (write mode) and auditing existing tests (review mode).

Explains MariaDB-specific CREATE INDEX and DROP INDEX syntax, including mapping to ALTER TABLE, prefix lengths for TEXT/BLOB, lack of expression indexes, real descending indexes, IGNORED indexes, and index kinds. Use when writing or reviewing index statements for MariaDB.

Use for writing, reviewing, debugging, or testing bounded retry policies in Python with Tenacity, including retry predicates, stop and wait strategies, jitter, exception propagation, callbacks, Retrying, and AsyncRetrying. Do not use for generic loops, scheduled jobs, domain polling without a retryable operation, or operations whose side effects are not safe to repeat.

Remove signs of AI-generated writing from academic medical papers. Use when editing or reviewing manuscripts to make them sound more natural and professionally written. Based on Wikipedia's "Signs of AI writing" guide, adapted for medical literature. Detects and fixes patterns including: inflated significance claims, superficial -ing analyses, vague attributions, AI vocabulary words, copula avoidance, excessive hedging, generic conclusions, informal word choices (linked/beyond/via/where/yield), overly assertive causal claims, and artificially condensed expressions. Preserves legitimate academic transitions (Notably, Prior studies have shown, etc.).

Explains MariaDB Connector/ODBC-specific behavior for application code, including DSN-less connection strings, positional parameter markers, prepared statement execution modes, autocommit defaults, TLS auto-enablement, and error handling. Use when writing or reviewing ODBC-based code (C/C++ or pyodbc) that talks to.

Use for writing, reviewing, debugging, testing, or analyzing Python SimPy discrete-event simulations. Trigger on Environment, Event, Process, timeout, Resource, PriorityResource, PreemptiveResource, Container, Store, queues, interrupts, simulation clocks, replications, or SimPy monitoring. Do not use for asyncio services, wall-clock schedulers, continuous ODE solvers, or Monte Carlo code without an event-process model.

Conduct a design interview, generate 5 distinct UI variations in a temporary route, collect real click-to-comment feedback on the live rendered variants via human-review, and produce an implementation plan. Use when the user wants to explore UI design options, redesign an existing component/page, or create new UI with multiple genuinely different approaches to compare — before writing production code or committing to a direction. For a lighter, single-component variant picker with no interview, use `prototype` instead. For reviewing a UI that's already real (not exploring new directions), use `visual-review`. Source: adapted from github.com/0xdesign/design-plugin's design-lab skill (interview + 5-variant structure), with feedback collection replaced by this repo's own `visual-review` skill (human-review) instead of a bespoke overlay component.

Use for writing, reviewing, debugging, or testing Python terminal presentation built with Rich, including Console streams, Text and markup safety, tables, trees, panels, progress, status, Live displays, render protocols, and deterministic output capture. Do not use for CLI argument parsing, structured logging design, browser UI, or machine-readable protocol output that must remain plain.

Use for writing, reviewing, debugging, testing, or optimizing Python CVXPY optimization models. Trigger on Variable, Parameter, Expression, Constraint, Objective, Problem, DCP, DPP, DGP, DQCP, solver selection/status, dual values, mixed-integer, cone, or repeated parametric solves. Do not use for scipy.optimize-only, PyMC inference, symbolic algebra without optimization, or hand-written solver implementations.

Use this skill when the user is working with Supabase and needs help with Edge Functions, SQL schema or migrations, Auth, Row Level Security, database functions, local CLI workflows, or deployment. Use it for building features, reviewing Supabase code, creating migrations, writing policies, implementing auth-aware server logic, and debugging full Supabase app flows.

Propose specific, actionable test cases for a target module — without writing the actual test code. Use this skill whenever the user wants to know "what should I test", "what test cases would catch real bugs in X", "I have a finding from test-assessment, what tests would close that gap", "suggest tests for this file", or wants to think through coverage before writing. Pairs with the test-assessment skill (which finds gaps); writing the test code itself happens as a normal follow-up task once the suggestions are reviewed. This skill stops at suggestions — if the user wants code generated, redirect them. Trigger even on casual phrasings ("what should I test in auth.ts", "give me test ideas for this module").

Use for writing, reviewing, debugging, testing, or optimizing Python SymPy symbolic mathematics. Trigger on Symbol, assumptions, Expr, Eq, solve/solveset, simplify, factor, expand, calculus, matrices, exact arithmetic, lambdify, code generation, or symbolic-to-numeric conversion. Do not use for NumPy-only arrays, mpmath-only arbitrary-precision numerics, CVXPY optimization models, or parsing untrusted mathematical text.

Use when writing, reviewing, debugging, or testing PowerShell `.ps1` scripts and advanced functions, including parameters, pipeline objects, streams, native commands, filesystem safety, PowerShell 7 portability, Pester, and PSScriptAnalyzer. Do not use merely to run an existing script, author Bash or batch files, package a module or DSC resource, or perform live system or tenant administration.

React and Next.js performance optimization patterns adapted from Vercel Engineering's React Best Practices (https://github.com/vercel-labs/agent-skills). Organizes 70+ rules across 8 priority categories — waterfalls, bundle size, server-side, client fetching, re-render, rendering, JS micro-perf, advanced. Use when writing, reviewing, or refactoring React/Next.js code for performance.

Use for writing, reviewing, debugging, or testing Python Streamlit apps, especially rerun behavior, widget identity and callbacks, session_state, cache_data/cache_resource, forms, fragments, containers, multipage navigation, uploads/downloads, and Streamlit-hosted chart/table interaction. Do not use for standalone Plotly/Altair figure design, generic backend services, Dash apps, or deployment configuration without app code.

Use for writing, reviewing, debugging, or testing publication-quality display tables in Python with Great Tables, including GT construction, stub and row groups, headers and spanners, labels, numeric/date formatting, targeted styles, footnotes/source notes, HTML/LaTeX/image export, and render verification. Do not use for dataframe computation, interactive data grids, charts, or plain console tables.

Apply world-class developer documentation principles (Stripe, Snowflake, Databricks, TiDB Cloud) to structure, write, review, or refactor technical documentation. Use this skill whenever the user mentions documentation, docs, sidebar or navigation, information architecture, restructuring a section, writing or editing a guide, reviewing docs, where content belongs, English doc prose, headings, code comments, link text, docs home pages, section landing pages, long-form guides mixing content types, cross-referencing, or making docs readable for AI agents and LLMs. Covers VeloDB Cloud docs work (Monitoring restructure, sidebar, EN/中文 alignment, writing style, landing pages, LLM-friendly docs) and any SaaS or database documentation task. Trigger broadly: if the conversation touches doc organization, page structure, doc quality, doc sentences, landing pages, or AI-readable docs, consult this skill rather than answering from intuition.

Structured methodology for solving, writing, and presenting hiring case studies for Senior Product Manager and Technical PM roles. Use when resolving a case study, reviewing a case study response, or building a presentation prototype from a completed case study. Covers the full process from problem understanding to final delivery, including data analysis, written response, and interactive presentation.

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.

Use for writing, reviewing, debugging, or testing Python JSON serialization and deserialization with orjson, including bytes/text boundaries, datetimes, dataclasses, NumPy, custom default handlers, option flags, strictness, and web/file integration. Do not use for JSON Schema validation, format-preserving JSON edits, streaming I/O frameworks, or choosing a JSON library when orjson is not requested or present.

Use for writing, reviewing, debugging, migrating, or testing Python application configuration built with pydantic-settings. Trigger for BaseSettings, SettingsConfigDict, environment names, dotenv, secrets directories, nested settings, CLI sources, custom source precedence, and secret-safe startup configuration. Do not use for ordinary Pydantic model validation, direct os.environ access in a small script, or external secret manager administration.

Clinic-architecture-aligned iOS animation craft guidelines for SwiftUI (iOS 26 / Swift 6.2) covering motion tokens, spring physics, gesture continuity, spatial transitions, micro-interactions, and accessibility. Enforces @Equatable on animated views and keeps animation state aligned with Domain/Data feature boundaries. Use when writing, reviewing, or refactoring SwiftUI animation code under the clinic modular MVVM-C architecture.

PROACTIVE SKILL — automatically apply whenever writing, generating, or editing any text that is mainly in Chinese. No user trigger needed. Also use when the user explicitly asks to "fix Chinese", "修改中文", "去翻译腔", "去AI味", "fix Chinese formatting", or "review Chinese text". Eliminates AI-sounding expressions and translation artifacts. Enforces Chinese-English mixed formatting rules (spacing, punctuation, bold formatting).

Audits and enforces web interface standards covering accessibility, performance, UX, and code quality from Vercel Engineering's Web Interface Guidelines. Use this skill when reviewing UI code, checking accessibility compliance, auditing design implementations, running pre-merge frontend checks, or when someone asks to "review my UI", "check accessibility", "check my site", "audit design", or "is this component correct". Apply proactively when writing form elements, interactive components, images, animations, or anything that users directly touch — these guidelines prevent common mistakes before they reach production.

Audits codebases for common security vulnerabilities that AI coding assistants introduce in "vibe-coded" applications. Checks for exposed API keys, broken access control (Supabase RLS, Firebase rules), missing auth validation, client-side trust issues, insecure payment flows, and more. Use this skill whenever the user asks about security, wants a code review, mentions "vibe coding", or when you're writing or reviewing code that handles authentication, payments, database access, API keys, secrets, or user data — even if they don't explicitly mention security. Also trigger when the user says things like "is this safe?", "check my code", "audit this", "review for vulnerabilities", or "can someone hack this?".

When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," or "find out why customers churn/convert/buy." Use for both analyzing existing research assets AND gathering new research from online sources. For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.

Resolves an approved article comment task into a publishable AI markdown reply by fetching article context from a local HTTP API (with sf-cli fallback), reasoning with the selected quote and full article content, and writing the final reply to a backend-provided local result file path.

English LaTeX academic paper assistant for existing `.tex` projects. Use this skill whenever the user wants to compile, lint, audit, or improve an English LaTeX conference or journal paper such as IEEE, ACM, Springer, NeurIPS, or ICML submissions. Trigger even when the user only mentions one paper issue, such as bibliography errors, grammar cleanup, sentence splitting, logic review, expression polishing, translation, title optimization, figure checks, pseudocode review, algorithm block cleanup, de-AI editing, or experiment-section review. Also trigger for "proofread my paper", "fix my LaTeX", "prepare for submission", "check my manuscript", "improve my writing", `algorithm2e`, `algorithmicx`, `algpseudocodex`, `Require/Ensure`, or "Algorithm 1" when the user has a .tex file.

App Store Optimization for mobile launches (iOS App Store, Google Play). Use when preparing a mobile app launch, optimizing app store listings, planning screenshot sequences, writing app store copy, doing keyword research for app stores, planning preview videos, managing reviews, or A/B testing app store assets. Relevant for Expo/React Native apps going to stores. Not for web-only products.

Use for writing, configuring, integrating, reviewing, debugging, or testing Python structured logging with structlog. Trigger for bound loggers, event dictionaries, processor chains, JSON or console rendering, standard-library logging integration, contextvars, request correlation, exception rendering, and structlog test capture. Do not use for stdlib-logging-only, Loguru-only, metrics-only, tracing-only, or collector configuration tasks that do not use structlog.

Supervises theses and dissertations end to end — structure guidance from proposal through defense, chapter-by-chapter writing support (introduction, literature review, methodology, results, discussion), supervision strategies, committee management, defense and viva voce preparation, timeline planning, feedback integration, examiner-expectation guidance, and formatting (APA 7, Chicago, university styles). Use when the request mentions thesis, dissertation, supervision, defense preparation, viva, proposal defense, thesis structure, thesis chapter, literature review chapter, methodology chapter, results chapter, discussion chapter, thesis timeline, committee, thesis formatting, or dissertation proposal. Part of the AlterLab Academic Skills suite.

Generate academic research proposals for PhD applications. Use when user asks to "write a research proposal", "create PhD proposal", "generate research plan", "撰写研究计划", "写博士申请", "doctoral proposal", or mentions specific research topics for PhD application. Supports STEM, humanities, and social sciences with field-specific adaptations. Follows Nature Reviews-style academic writing conventions. Supports both English and Chinese output based on user preference.

Performs deep architectural analysis of a specified module, directory, or feature area by examining structural coupling, data flow, concurrency patterns, risk, and SOLID alignment. Use when the user wants to assess, evaluate, or review the architecture, design quality, dependency structure, coupling, cohesion, or technical debt of an existing part of the codebase. Not for investigating specific bugs, runtime errors, or failures — use investigate. Not for test planning — use automated-test-planning. Not for file-level code review — use code-review. Not for researching open-ended options, prior art, or how something works — use research. Not for designing a new interface or contract — use design-an-api. Not for writing documentation or architectural decision records.

Build work collaboratively in reviewable pieces, handing each piece back for review before starting the next, so the person stays in the lead and steers while the work happens instead of reviewing a finished result. Use when someone says to pair with them on something, asks to collaborate rather than direct, wants to review as it goes, or wants to guide the work piece by piece — on code, on a design decision, or on writing. For a test-first build it runs tdd, for restructuring it runs refactor, for an interface contract it runs design-an-api, and for plan work it runs iterative-plan-review or plan-implementation, each collaboratively; invoke any of those directly instead to run it straight through without pausing. Does not pace someone through code that already exists and builds nothing — use code-walkthrough. Does not explain, summarize, or research something instead of producing it — use code-overview or research.

When the user wants to edit, review, or improve existing marketing copy, or refresh outdated content. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' 'copy sweep,' 'tighten this up,' 'this reads awkwardly,' 'clean up this text,' 'too wordy,' 'sharpen the messaging,' 'refresh this content,' 'update this page,' 'this content is outdated,' or 'content audit.' Use this when the user already has copy and wants it improved or refreshed rather than rewritten from scratch. For writing new copy, see copywriting.