renovate
Assists with automating dependency updates across JavaScript, Python, Docker, Go, Rust, Terraform, and 50+ ecosystems using Renovate. Use when configuring update strategies, automerge policies, grouping rules, or scheduling to keep dependencies current. Trigger words: renovate, dependency updates, automerge, package rules, dependency management.
What this skill does
# Renovate ## Overview Renovate is an automated dependency update tool that scans repositories for dependency files across 50+ ecosystems (npm, pip, Docker, Go, Rust, Terraform, GitHub Actions) and creates pull requests with changelogs, release notes, and configurable automerge policies. It supports grouping, scheduling, and per-package rules to keep dependencies current without overwhelming teams. ## Instructions - When setting up Renovate, start with `config:recommended` which provides sensible defaults for grouping, scheduling, and automerge, then add `renovate.json` to the repo root. - When configuring automerge, enable it for low-risk updates (`@types/*`, devDependencies patches) and disable it for major updates, using `platformAutomerge` for GitHub's native merge feature. - When reducing PR noise, use `group:allNonMajor` for a single weekly PR covering all minor and patch updates, and group monorepo packages (React, Angular, Babel) together. - When setting schedules, configure update windows for low-traffic times (e.g., `["after 9am and before 5pm every weekday"]`) to avoid disrupting developers. - When defining package rules, use `matchPackageNames`, `matchPackagePatterns`, and `matchUpdateTypes` to set per-package automerge, grouping, and version strategies. - When handling version strategies, pin exact versions in applications for reproducibility and use ranges in libraries for compatibility. ## Examples ### Example 1: Configure Renovate for a production monorepo **User request:** "Set up Renovate with automerge for safe updates and weekly batching" **Actions:** 1. Create `renovate.json` extending `config:recommended` and `schedule:weekly` 2. Add package rules to automerge `@types/*` and devDependency patches 3. Group React, Next.js, and testing library packages into single PRs 4. Enable the dashboard issue for an overview of all pending updates **Output:** A Renovate configuration that automerges safe updates, batches non-major changes weekly, and groups related packages. ### Example 2: Manage Docker and Terraform dependency updates **User request:** "Keep Docker base images and Terraform provider versions up to date" **Actions:** 1. Configure Renovate to scan Dockerfiles and `.tf` files 2. Set `matchDatasources: ["docker"]` with `automerge: false` for base image updates 3. Group Terraform providers by cloud provider (AWS, GCP, Azure) 4. Enable vulnerability alerts to prioritize updates that fix known CVEs **Output:** Automated PRs for Docker and Terraform dependency updates with grouped providers and security prioritization. ## Guidelines - Start with `config:recommended` since it handles grouping, scheduling, and automerge sensibly. - Automerge `@types/*` and devDependencies patches since they are low-risk and high-volume. - Group monorepo packages (React, Vue, Angular, Babel, Jest) into single PRs to reduce noise. - Schedule updates for low-traffic times to avoid disrupting developers during peak hours. - Pin exact versions in applications and use ranges in libraries. - Review major updates manually since breaking changes require human judgment.
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.