5.1K skills · sorted by relevance
Transfer known function and variable names from an older binary to a newer version. Compare disassembly and pseudocode with an LLM, produce structured mappings, and apply names and comments in IDA.
Build Helidon 4 applications on Java 21 or later with guidance for SE and MP. Apply practical patterns for HTTP endpoints, database access, configuration, testing, and security while accounting for API changes from Helidon 3.
Audit Secure Boot settings, revoked boot components, and EFI startup files on Linux and Windows. The skill helps identify missing protections and signs of bootkits, malicious software that runs before the operating system.
Review Cuckoo or AnyRun behavior reports for signs that malware is avoiding an analysis environment. Identify timing checks, virtual machine detection, and user activity checks, then produce a JSON report with evidence, technique mappings, and an evasion sophistication score.
Address existing feedback on a GitHub pull request, a proposed code change. Evaluate comments against the code, apply valid fixes, and verify replies and thread resolution, with options for local handoff or resuming saved work.
Set up and troubleshoot Daytona sandbox environments, which provide isolated spaces for running applications. The skill covers CLI authentication, persistent desktop and server sandboxes, diagnostic logs, shared secrets storage, snapshot refreshes, and environment deletion.
Roll back Kortix production to a previously released version using existing builds. Covers frontend and backend rollback, database compatibility checks, prevention of unintended frontend rebuilds, and returning to the latest version through a later release.
Run untrusted or AI-generated code in temporary microVMs, small virtual machines isolated from the host. Execute a snippet in one call, manage multi-step sessions, and read or edit files inside the sandbox.
Design MongoDB data structures around how data is accessed, write queries, and build staged data transformations for aggregation. Review indexes and query execution statistics to identify performance issues and choose suitable approaches for related or time-series data.
Plan data ingestion and transformation workflows with Apache Airflow, Spark, and dbt. Get guidance on processing changed records, validating data quality, and rerunning failed or historical jobs without creating duplicate results.
Compare proposed employee handbook wording with the current version, identify affected policies and state supplements, and flag reductions in promised benefits. Receive a change summary, impact tables, and a checklist for preparing publication.
Read comments and replies on a Canva design, turn feedback into an edit plan, and apply approved changes. Identify conflicting requests and edits requiring manual work, then provide a checklist and reply to reviewers with the outcome.
Build third-party tools to inspect, extract, migrate, or analyze DeepChat's local settings and conversations. Work through data locations, database encryption, and table relationships while favoring read-only copies and redacted output.
Build document search with AgentDB that finds related content by meaning. Store documents as numerical representations, combine similarity search with metadata filters, and retrieve relevant passages for systems that generate answers using source material.
Create AgentDB learning plugins that use recorded experience to improve agent decisions. Choose a learning method, store states, actions, and rewards, train models, and evaluate suggested actions through CLI and API workflows.
Collect experiment reports from issues and organize them in an existing Markdown index. It places entries in relevant sections, merges WandB experiment links into existing records, and checks for duplicate entries and formatting inconsistencies.
CloudBase declarative deployment from a cloudbaserc config (声明式部署, 配置式部署, cloudbaserc 部署) through the deployBuild / deployPlan / deployApply MCP tools. Use when deploying database, functions, app, hosting, or gateway resources described in cloudbaserc.json/yaml as a single desired-state config, when a user wants to build static hosting artifacts locally first (deployBuild), or wants a dry-run plan before applying (deployPlan), or when handling multi-environment deploys via mode / envOverrides. Covers build-plan-apply flow (deployBuild local build → deployPlan dry-run → deployApply confirm=true), hosting build-output neutralization, envId resolution priority, only/skip filtering, concurrency, and continueOnError. Prefer deployBuild (when hosting declares a buildCommand) and deployPlan before deployApply; do not confuse with per-resource tcb CLI deploy or single-function deploy.
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Unified CloudBase execution guide for all-in-one skill installs. Use this first for CloudBase app tasks, especially existing apps with TODOs, fixed pages, or active handlers. Routes PostgreSQL / CloudBase PG / app.rdb() / queryPgDatabase / managePgDatabase work away from legacy NoSQL and old auth patterns.
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Use when building, debugging, or evaluating CloudBase PostgreSQL / CloudBase PG / PG mode apps, including Postgres schema setup, queryPgDatabase/managePgDatabase, JS SDK v3 app.rdb() CRUD/RPC, PG HTTP API fallback, RLS-style permissions, username-password auth, and Web CMS/admin CRUD flows backed by CloudBase PG.
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火山引擎云数据库 VeDB MySQL 版（简称vedbm）管理技能。当用户需要创建 VEDB 实例、查询 VEDB 实例列表、查看实例详情、管理数据库账号、获取实例连接地址（Endpoints）、或对实例规格进行升级/降级时使用此技能。包含特定关键词：火山引擎云数据库、VEDBM、VeDB MySQL。
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Use when you need to add or review Mongock MongoDB data migrations in a Spring Boot application — including Maven coordinates, Spring Data MongoDB drivers, migration scan packages, @ChangeUnit classes, lock/transaction settings, and optional policy-approved MongoDB integration verification. This should trigger for requests such as Add Mongock migrations in Spring Boot; Review Spring MongoDB data migrations; Configure Mongock change units for Spring Data MongoDB; Create Mongock change units for Spring Boot MongoDB; Review Mongock migration ordering in a Spring service. Part of Plinth Toolkit
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Use when you need to use Spring Data JDBC with Java records — including entity design with records, repository pattern, immutable updates, aggregate relationships, custom queries, transaction management, and avoiding N+1 problems. This should trigger for requests such as Review Java code for Spring Data JDBC; Apply best practices for Spring Data JDBC in Java code; Model Spring Data JDBC aggregates with Java records; Review Spring Data JDBC repositories and aggregate boundaries; Improve optimistic locking or domain events in Spring Data JDBC. Part of Plinth Toolkit
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This skill should be used when the user asks to "process beta reader feedback", "alpha reader feedback", "feedback round", "synthesize reader feedback", "reader notes", "beta feedback", "reader readiness check", "review copy", "send the draft to readers", "share with readers who don't use GitHub", "triage the reader panel", or wants to collect, reconcile, and act on external reader feedback for a story project. NOT for running the simulated reader panel itself (use reader-panel), rounds with a professional editor (use editorial-review), or for checking a manuscript is ready to query or publish (use submission or publishing).
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DuckDBを使用した大規模データ分析の専門スキル。DuckDBのアーキテクチャ、SQL構文、パフォーマンス最適化、各種ファイル形式（CSV、Parquet、JSON等）の効率的な読み込み・書き出しを熟知。メモリ効率の良い分析、複雑なクエリの最適化、データパイプライン構築を支援。Use when analyzing large datasets, querying CSV/Parquet/JSON files directly, building data pipelines, or optimizing analytical queries with DuckDB.
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