skills.oriz.in

22 agent skills. Junction into ~/.claude/skills/ via agent-skills submodule. RSS · llms.txt

• agent-browser — Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
• code-research — Research open-source repositories to understand how something is built or works.
• cross-review — Cross review code using a subagent with a specified model. Use when the user asks to review code changes AND specifies a model to use (e.g., 'review with opus', 'use sonnet to review', 'review changes with gemini'). The key differentiator from the regular zen-review skill is that the user explicitly specifies which model should perform the review. The root agent reconstructs what changed from its own conversation history — no git commands are used.
• develop-userscripts — Use when building, debugging, packaging, or publishing browser userscripts for Tampermonkey or ScriptCat, including GM APIs, metadata blocks, permission issues, @match/@grant/@connect setup, ScriptCat background or scheduled scripts, UserConfig blocks, or subscription workflows.
• explore — Use this skill when the user asks you something that requires searching a code base
• feature-research — Research existing architecture before implementing a complex feature.
• find-skills — Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
• frontend-design — Design distinctive, production-grade frontend interfaces — mockups as HTML pages or working application pages. Use when the user asks to design a web page, landing page, UI mockup, dashboard, application page, or any visual HTML interface. Supports single designs, multiple variant generation, and integration with existing project frameworks.
• grill-me — Interview the user relentlessly about a plan or design until reaching shared understanding, resolving every branch of the decision tree. Use when the user wants to stress-test a plan, get grilled on their design, or explicitly says "grill me."
• init — Use when the user asks to initialize a repo, create AGENTS.md, generate contributor guidelines, or set up agent-oriented documentation for a codebase.
• microsoft-foundry — Deploy, evaluate, fine-tune, and manage Foundry agents end-to-end with azd: hosted agent scaffold/run/deploy, prompt agent create, batch eval, continuous eval, prompt optimizer, Agent Optimizer scaffold, agent.yaml, dataset curation from traces, model fine-tuning (SFT/DPO/RFT). USE FOR: azd ai agent, azd provision/deploy, deploy agent, hosted agent, create agent, add tool to agent, invoke agent, evaluate agent, continuous eval, continuous monitoring, optimize prompt, improve prompt, optimize agent instructions, agent optimizer, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, AI Services, create Foundry resource, provision, knowledge index, customize deployment, onboard, availability, fine-tune, SFT, DPO, RFT, training-data, grader, distillation, fine-tuned model, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
• pieces-mcp — Pieces MCP server tool guide. Use for long-term memory, workstream search, filesystem access, browser history, calendar, and more.
• plan — Planning agent for task breakdown and implementation planning. Use via spawn_subagent with skill='plan' when you need to explore a codebase and design an implementation approach before writing code.
• research — Fast agent specialized for exploring codebases and searching for code patterns. Use via spawn_subagent with skill='research' for read-only exploration tasks.
• search-everything — Comprehensive multi-source research on any topic. Use when the user says "search everything about X", "find all issues about X", "what exists for X", or before filing any issue/PR to ensure no dupes exist. Fans out to GitHub, web, knowledge/, npm/registry, and URL-reads in parallel.
• skill-compact — Analyze, deduplicate, and restructure agent skills to follow agentskills.io best practices. Merges duplicate skills, extracts shared content into references, reduces SKILL.md sizes, and tracks original sources for update-then-recompact workflows. Use when the user mentions "compact skills", "deduplicate skills", "merge skills", "skill bloat", "too many skills", "skill cleanup", or "optimize skills". Integrates with openskills, skills.sh, and skillshare CLIs.
• skill-creator — Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
• smithery-ai-cli — Find, connect, and use MCP tools and skills via the Smithery CLI. Use when the user searches for new tools or skills, wants to discover integrations, connect to an MCP, install a skill, or wants to interact with an external service (email, Slack, Discord, GitHub, Jira, Notion, databases, cloud APIs, monitoring, etc.).
• tdd — Red-Green-Refactor TDD loop for AI-implemented features. Writes ONE failing test first, verifies red, minimum code to green, then refactors. Blocks AI test-cheating (writing tests AFTER implementation to match code, not spec).
• use-my-browser — Use when work depends on the user's live browser session or visible rendered state rather than static fetches, especially for browser debugging contexts or DevTools-selected elements or requests, logged-in dashboards or CMS flows, localhost apps, forms, uploads, downloads, media inspection, DOM or iframe inspection, Shadow DOM, or browser failures that look like soft 404s, auth walls, anti-bot checks, or rate limits.
• zen-comprehensive-review — Orchestrate a multi-model code review: spawn 3 review subagents, merge findings. In PR mode, posts GitHub PR comments. In local mode, outputs findings directly. CRITICAL: this skill is costly, don't use it unless user explicitly requested to use it.
• zen-review — Expert code reviewer. Analyze PR changes for correctness, security, performance, and quality. Returns findings as JSON. CRITICAL: this skill is costly, don't use it unless user explicitly requested to use it.