3.8K skills · sorted by relevance
Learn to create, discover, invoke, secure, evaluate, package, and port Agent Skills through one interactive lesson at a time. Practical checkpoints and quizzes track demonstrated progress in a local file, so later sessions resume where you stopped.
🛒 E-commerce & Retail skill suite derived from VoltAgent/awesome-agent-skills. Product catalogue optimisation, conversion rate, customer journey and retail analytics. Provides 10 specialised commands for ecommerce, retail, shopify workflows.
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📈 SEO & Content Marketing skill suite derived from VoltAgent/awesome-agent-skills. Keyword research, content audits, SERP analysis, technical SEO and content strategy. Provides 10 specialised commands for seo, content, marketing workflows.
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Choose the right engineering skills for a task and decide their order, from clarifying requirements to deployment. This guide also defines shared practices for stating assumptions, resolving uncertainty, keeping scope focused, and verifying completed work.
Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill, audit this skill, is this skill safe, vet a skill before installing, what does this skill access. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, spec validation, and security auditing of third-party skills before install.
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Use when installing skills from a shared ai-agent-skills library repo. Inspect with `--list` first, prefer `--collection`, and preview with `--dry-run` before installing.
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Use when exploring the ai-agent-skills catalog to find, compare, and evaluate skills before installing. Always use --fields to limit output size and --dry-run before committing to an install.
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Scaffold a new SciAgent-Skills entry. Picks pipeline/toolkit/database/guide template, creates skills/{category}/{name}/SKILL.md with valid frontmatter, appends the registry.yaml entry, runs validation. Enforces name uniqueness, kebab-case, description keyword rules, schema rules from AGENTS.md. TRIGGER when user says (any language): "add a SciAgent skill", "add a skill for <X>", "create new skill", "create a SKILL.md for <X>", "scaffold a skill", "new skill entry", "register a skill", "신규 skill 추가", "스킬 만들어줘", "스킬 생성", "skill 만들어", or any request to add a new SKILL.md to this repo. ALWAYS invoke this skill BEFORE writing to skills/ or registry.yaml. DO NOT TRIGGER when: editing existing entry's content (just edit the file directly); migrating an existing entry (read AGENTS.md "Migrating from Existing Entries" first); only updating registry.yaml without creating a new SKILL.md.
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Discover and invoke 1,676 deduplicated biomedical AI agent skills from the Awesome Bio Agent Skills repository (20 source repos, 15 categories). Use this skill as a router whenever a user needs a bioinformatics/biomedical task (genomics, transcriptomics, single-cell, proteomics, protein design, clinical, epigenomics, multi-omics, pathway, metagenomics, database queries, visualization, workflows): search the index, locate the best-matching skill, fetch its SKILL.md, and follow it.
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Static human-browsable catalog of the Zephyr RTOS skill set. Skill selection is handled by the zephyr-agent-skills entry point and by zephyr-cli skills suggest; this index is a reference listing only, not a task skill.
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Zephyr RTOS development — boards and devicetree, the build system (west, Kconfig, CMake, sysbuild), drivers and peripherals, BLE and networking, the kernel, storage, power, testing and debugging, security and OTA. Use this for ANY Zephyr RTOS or embedded-firmware task on a Zephyr project; it routes you to the right specialized skill via the zephyr-cli registry.
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Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill, audit this skill, is this skill safe, vet a skill before installing, what does this skill access. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, spec validation, and security auditing of third-party skills before install.
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Discovers and invokes agent skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.
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Review code using shared OpenClaw instructions and a Python helper, while also following the target repository’s review requirements. This skill points to a common installation that supplies the actual review procedure.
Review and refactor React and Next.js code to address slow loading and interactions. Prioritized guidance covers sequential data requests, downloaded JavaScript size, server processing, repeated rendering, and browser work, with examples for choosing relevant improvements.
Set up automated checks and deployment workflows with GitHub Actions. Covers tests, type checks, builds, security audits, preview deployments, staged releases, and rollback plans, with guidance for diagnosing failures and reducing pipeline runtime.
Plan the retirement of old APIs, features, and systems, then move their users to replacements in stages. The skill also guides database schema changes through additive steps that keep old and new application code compatible during rollout.
Prepare a production release with checks for code quality, security, performance, accessibility, and infrastructure. Plan monitoring, gradual feature exposure, and rollback steps, then use release metrics and reliability limits to guide rollout decisions.
Document why software decisions were made, which alternatives were considered, and what trade-offs remain. Create architecture decision records, README guidance, API documentation, and changelogs that help future contributors and AI agents understand the project.
Challenge important design and implementation decisions with a separate reviewer that does not inherit the working session's context. Identify hidden assumptions and failure cases, then assess each finding against the artifact and its requirements.
Define project quality standards in CONSTRAINTS.md, connect measurable targets to checks, and inspect changes for weakened safeguards. It helps teams choose thresholds and catch skipped tests, suppressed warnings, unfinished code, or lowered standards during agent development.
Clarify an unclear request through one question at a time, with the agent sharing its best guess for each answer. Produce a user-confirmed statement covering the desired outcome, audience, timing, success criteria, constraints, and exclusions.
Find and fix slow page loads, API responses, and database queries using measurements. Compare results before and after each change, discard changes without clear gains, and add checks or monitoring to catch future slowdowns.
Turn clear requirements into small implementation tasks with acceptance criteria, verification steps, dependencies, and estimated scope. Produce a written plan and ordered task list, with checkpoints and opportunities for parallel work identified before coding begins.