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asc-crash-triage

Triage TestFlight crashes, beta feedback, and performance diagnostics using asc. Use when the user asks about TF crashes, TestFlight crash reports, beta tester feedback, app hangs, disk writes, launch diagnostics, or wants a crash summary for a build or app.

rudrankriyam
rudrankriyam
71938

asc-id-resolver

Resolve App Store Connect IDs (apps, builds, versions, groups, testers) from human-friendly names using asc. Use when commands require IDs.

rudrankriyam
rudrankriyam
71938

asc-localize-metadata

Automatically translate and sync App Store metadata (description, keywords, what's new, subtitle) to multiple languages using LLM translation and asc CLI. Use when asked to localize an app's App Store listing, translate app descriptions, or add new languages to App Store Connect.

rudrankriyam
rudrankriyam
71938

asc-metadata-sync

Sync and validate App Store metadata and localizations with asc, including legacy metadata format migration. Use when updating metadata or translations.

rudrankriyam
rudrankriyam
71938

asc-notarization

Archive, export, and notarize macOS apps using xcodebuild and asc. Use when you need to prepare a macOS app for distribution outside the App Store with Developer ID signing and Apple notarization.

rudrankriyam
rudrankriyam
71938

asc-ppp-pricing

Set territory-specific pricing for subscriptions and in-app purchases using current asc setup, pricing summary, price import, and price schedule commands. Use when adjusting prices by country or implementing localized PPP strategies.

rudrankriyam
rudrankriyam
71938

asc-xcode-build

Build, archive, export, and manage Xcode version/build numbers with asc and xcodebuild before uploading to App Store Connect. Use when you need to create an IPA or PKG for upload.

rudrankriyam
rudrankriyam
71938

customaize-agent:create-hook

Create and configure git hooks with intelligent project analysis, suggestions, and automated testing

neolabhq
neolabhq
71860

kaizen:plan-do-check-act

Iterative PDCA cycle for systematic experimentation and continuous improvement

neolabhq
neolabhq
71860

kaizen:root-cause-tracing

Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior

neolabhq
neolabhq
71860

kaizen:why

Iterative Five Whys root cause analysis drilling from symptoms to fundamentals

neolabhq
neolabhq
71860

mcp:build-mcp

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

neolabhq
neolabhq
71860

mcp:setup-arxiv-mcp

Guide for setup arXiv paper search MCP server using Docker MCP

neolabhq
neolabhq
71860

mcp:setup-codemap-cli

Guide for setup Codemap CLI for intelligent codebase visualization and navigation

neolabhq
neolabhq
71860

mcp:setup-context7-mcp

Guide for setup Context7 MCP server to load documentation for specific technologies.

neolabhq
neolabhq
71860

mcp:setup-serena-mcp

Guide for setup Serena MCP server for semantic code retrieval and editing capabilities

neolabhq
neolabhq
71860

reflexion:critique

Comprehensive multi-perspective review using specialized judges with debate and consensus building

neolabhq
neolabhq
71860

reflexion:memorize

Curates insights from reflections and critiques into CLAUDE.md using Agentic Context Engineering

neolabhq
neolabhq
71860

reflexion:reflect

Reflect on previus response and output, based on Self-refinement framework for iterative improvement with complexity triage and verification

neolabhq
neolabhq
71860

sadd:do-and-judge

Execute a task with sub-agent implementation and LLM-as-a-judge verification with automatic retry loop

neolabhq
neolabhq
71860

sadd:do-competitively

Execute tasks through competitive multi-agent generation, meta-judge evaluation specification, multi-judge evaluation, and evidence-based synthesis

neolabhq
neolabhq
71860

sadd:do-in-parallel

Launch multiple sub-agents in parallel to execute tasks across files or targets with intelligent model selection, quality-focused prompting, and meta-judge → LLM-as-a-judge verification

neolabhq
neolabhq
71860

sadd:do-in-steps

Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, meta-judge → LLM-as-a-judge verification

neolabhq
neolabhq
71860

sadd:judge-with-debate

Evaluate solutions through multi-round debate between independent judges until consensus

neolabhq
neolabhq
71860

sadd:judge

Launch a meta-judge then a judge sub-agent to evaluate results produced in the current conversation

neolabhq
neolabhq
71860

sadd:launch-sub-agent

Launch an intelligent sub-agent with automatic model selection based on task complexity, specialized agent matching, Zero-shot CoT reasoning, and mandatory self-critique verification

neolabhq
neolabhq
71860

sadd:multi-agent-patterns

Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.

neolabhq
neolabhq
71860

sadd:subagent-driven-development

Use when executing implementation plans with independent tasks in the current session or facing 3+ independent issues that can be investigated without shared state or dependencies - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates

neolabhq
neolabhq
71860

sadd:tree-of-thoughts

Execute tasks through systematic exploration, pruning, and expansion using Tree of Thoughts methodology with meta-judge evaluation specifications and multi-agent evaluation

neolabhq
neolabhq
71860

sdd:add-task

creates draft task file in .specs/tasks/draft/ with original user intent

neolabhq
neolabhq
71860

sdd:brainstorm

Use when creating or developing, before writing code or implementation plans - refines rough ideas into fully-formed designs through collaborative questioning, alternative exploration, and incremental validation. Don't use during clear 'mechanical' processes

neolabhq
neolabhq
71860

sdd:create-ideas

Generate ideas in one shot using creative sampling

neolabhq
neolabhq
71860

sdd:implement

Implement a task with automated LLM-as-Judge verification for critical steps

neolabhq
neolabhq
71860

sdd:plan

Refine, parallelize, and verify a draft task specification into a fully planned implementation-ready task

neolabhq
neolabhq
71860

tdd:fix-tests

Systematically fix all failing tests after business logic changes or refactoring

neolabhq
neolabhq
71860

tdd:test-driven-development

Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure first

neolabhq
neolabhq
71860

tdd:write-tests

Systematically add test coverage for all local code changes using specialized review and development agents. Add tests for uncommitted changes (including untracked files), or if everything is commited, then will cover latest commit.

neolabhq
neolabhq
71860

tech-stack:add-typescript-best-practices

Setup TypeScript best practices and code style rules in CLAUDE.md

neolabhq
neolabhq
71860

code-review:review-local-changes

Comprehensive review of local uncommitted changes using specialized agents with code improvement suggestions

neolabhq
neolabhq
71860

code-review:review-pr

Comprehensive pull request review using specialized agents

neolabhq
neolabhq
71860

customaize-agent:agent-evaluation

Evaluate and improve Claude Code commands, skills, and agents. Use when testing prompt effectiveness, validating context engineering choices, or measuring improvement quality.

neolabhq
neolabhq
71860

customaize-agent:apply-anthropic-skill-best-practices

Comprehensive guide for skill development based on Anthropic's official best practices - use for complex skills requiring detailed structure

neolabhq
neolabhq
71860

customaize-agent:context-engineering

Understand the components, mechanics, and constraints of context in agent systems. Use when writing, editing, or optimizing commands, skills, or sub-agents prompts.

neolabhq
neolabhq
71860

customaize-agent:create-agent

Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns

neolabhq
neolabhq
71860

customaize-agent:create-command

Interactive assistant for creating new Claude commands with proper structure, patterns, and MCP tool integration

neolabhq
neolabhq
71860

customaize-agent:create-rule

Use when found gap or repetative issue, that produced by you or implemenataion agent. Esentially use it each time when you say "You absolutly right, I should have done it differently." -> need create rule for this issue so it not appears again.

neolabhq
neolabhq
71860

customaize-agent:create-skill

Guide for creating effective skills. This command should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations. Use when creating new skills, editing existing skills, or verifying skills work before deployment - applies TDD to process documentation by testing with subagents before writing, iterating until bulletproof against rationalization

neolabhq
neolabhq
71860

customaize-agent:create-workflow-command

Create a workflow command that orchestrates multi-step execution through sub-agents with file-based task prompts

neolabhq
neolabhq
71860

customaize-agent:prompt-engineering

Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.

neolabhq
neolabhq
71860

customaize-agent:test-prompt

Use when creating or editing any prompt (commands, hooks, skills, subagent instructions) to verify it produces desired behavior - applies RED-GREEN-REFACTOR cycle to prompt engineering using subagents for isolated testing

neolabhq
neolabhq
71860

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Adoption

Agent Skills are supported by leading AI development tools.

FAQ

Frequently asked questions about Agent Skills.

01

What are Agent Skills?

Agent Skills are reusable, production-ready capability packs for AI agents. Each skill lives in its own folder and is described by a SKILL.md file with metadata and instructions.

02

What does this agent-skills.md site do?

Agent Skills is a curated directory that indexes skill repositories and lets you browse, preview, and download skills in a consistent format.

03

Where are skills stored in a repo?

By default, the site scans the skills/ folder. You can also submit a URL that points directly to a specific skills folder.

04

What is required inside SKILL.md?

SKILL.md must include YAML frontmatter with at least name and description. The body contains the actual guidance and steps for the agent.

05

How can I submit a repo?

Click Submit in the header and paste a GitHub URL that points to a skills folder. We’ll parse it and add any valid skills to the directory.