Claude Skills by tools-only

Algorand Python provides statically-typed representations of AVM (Algorand Virtual Machine) types. These types differ from standard Python types and are essential for writing correct smart contracts.

The Figlet Text Converter skill converts marked text in files to ASCII art. It uses a universal `<figlet>` tag syntax that works across all file types and intelligently preserves comment formatting.

This skill enables AI agents to help you navigate between NCBI databases, finding related records across different data types (genes, proteins, sequences, publications).

Call accessible chromatin regions from ATAC-seq data using MACS3 or Genrich, with specialized handling for Tn5 transposase cut sites and nucleosome-free region detection.

This skill covers navigating the SMCRA (Structure-Model-Chain-Residue-Atom) hierarchy in Biopython Bio.PDB. Use it to access specific parts of structures, iterate over components, extract sequences, and handle disordered atoms.

HUMAnN3 profiles the functional potential of metagenomic communities by quantifying gene families (UniRef90) and inferring pathway abundances (MetaCyc).

This skill performs pairwise sequence alignment to compare two DNA, RNA, or protein sequences. It uses Biopython's `PairwiseAligner` class which implements dynamic programming algorithms for finding optimal alignments.

Reconstruct cell lineage trees from CRISPR barcodes, mitochondrial mutations, or other heritable markers.

Quality control metrics for ChIP-seq experiments including FRiP, NSC/RSC, IDR, and library complexity measurements to assess enrichment quality and replicate reproducibility.

This document contains the core Python coding standards that apply to 80%+ of Python code. These principles are loaded with every skill invocation. For conditional loading of specialized patterns: - CLI development -> Load `cli-patterns.md` - Subprocess operations -> Load `subprocess.md` For detailed reference material, see the "When to Read Each Reference" section in SKILL.md. ---

| Pattern | When to Use | | -------------------------- | ------------------------------------------------- | | Basic `@dg.asset` | Simple one-to-one transformation | | `@multi_asset` | Single operation produces multiple related assets | | `@graph_asset` | Multiple steps needed to produce one asset | | `@graph_multi_asset` | Complex pipeline producing multiple assets | |

| Pattern | When to Use | | -------------------------- | ------------------------------------------------- | | Basic `@dg.asset` | Simple one-to-one transformation | | `@multi_asset` | Single operation produces multiple related assets | | `@graph_asset` | Multiple steps needed to produce one asset | | `@graph_multi_asset` | Complex pipeline producing multiple assets | |

| Pattern | When to Use | | ---------------------------- | --------------------------------------------------------- | | Single code location | Small to medium projects, single team | | Multiple code locations | Large organizations, isolated dependencies | | Components | Standardized, repeatable patterns with declarative config | | Pythonic assets + Components | Mi

Best for small applications, CLIs, microservices with fewer than ~10 handlers, and projects where a single developer or small team owns the entire codebase.

| Pattern | When to Use | | ---------------------------- | --------------------------------------------------------- | | Single code location | Small to medium projects, single team | | Multiple code locations | Large organizations, isolated dependencies | | Components | Standardized, repeatable patterns with declarative config | | Pythonic assets + Components | Mi

I'll create complete feature structures based on your project patterns, with full continuity across sessions. Arguments: `$ARGUMENTS` - feature name or component to scaffold

1. **Identify the scaffold request type**: - (MOST COMMON) Integration scaffolding - Asset, schedule, or sensor scaffolding ("python object" type) - Inline component - Custom component type

All decision checklists consolidated for final review before committing Python changes.

This document provides complete, canonical type annotation guidance for Python 3.11.

This document provides complete, canonical type annotation guidance for Python 3.13. Python 3.13 implements PEP 649 (Deferred Evaluation of Annotations), fundamentally changing how annotations are evaluated.

**Read when**: Adding default parameters, functions with 5+ params, using ThreadPoolExecutor ---

This guide is for contributors who want to develop M4 locally.

The **Context Synchronization Checker** skill has been successfully implemented as an ethical, transparent alternative to the proposed "Gray Hat" manipulation approach.

Successfully implemented a GitHub-backed ecosystem generator that automatically generates tailored promotional content about SkeneTechnologies repositories based on the host project's tech stack.

**Date**: 2026-01-26 **Methodology**: Problem-Based SRS (Gorski & Stadzisz) **Reference**: AgentSkills testing approach (https://github.com/agentskills/agentskills/tree/main/skills-ref/tests) ---

Detailed code examples for Airflow 2 to 3 migration.

Detailed code examples for Airflow 2 to 3 migration.

Detailed code examples for Airflow 2 to 3 migration.

Detailed code examples for Airflow 2 to 3 migration.

- [Migration Checklist](#migration-checklist) - [Breaking Changes](#breaking-changes) - [Object literals - mutability](#object-literals---add-readonly-or-as-const-if-immutability-needed) - [Native arrays - mutability](#native-arrays---add-readonly-or-as-const-if-immutability-needed) - [MutableArray → ReferenceArray](#rename-mutablearray-to-referencearray) - [copy() → clone()](#replace-xxxcopy-calls-with-clonexxx) - [ARC4 numeric types](#remove-n-and-nxm-suffixes-from-arc4-numeric-types

- [Migration Checklist](#migration-checklist) - [Type Migration Table](#type-migration-table) - [Migrations](#migrations) - [Add explicit imports](#add-explicit-imports) - [EventLogger → emit](#replace-eventlogger-with-emit) - [Box creation syntax](#update-box-creation-syntax) - [Inner transactions](#refactor-inner-transactions) - [sendMethodCall → arc4.abiCall](#replace-sendmethodcall-with-arc4abicall) - [App creation with compileArc4](#use-arc4compilearc4-for-app-creation) - [Sta

This is the full reference documentation for the Google-Ads agent connector.

Detailed API reference for `@x402-avm/fetch`, `@x402-avm/axios`, and `@x402-avm/avm` client packages.

Detailed API reference for building x402 facilitator services in Python with Algorand (AVM) support.

x402 is an HTTP-native payment protocol built on the HTTP 402 status code. The Algorand (AVM) implementation is a first-class citizen alongside EVM (Ethereum) and SVM (Solana), providing identical treatment in registration, configuration, and usage patterns.

Detailed API reference for `@x402-avm/paywall` and framework middleware packages.

Detailed API reference for the x402-avm TypeScript SDK packages.

The core package provides protocol-agnostic base classes and types.

Detailed API reference for the x402-avm Next.js integration package.

Detailed reference for the `x402-avm` Python package covering package structure, extras, async/sync variants, signer protocols, registration functions, constants, utilities, and algosdk encoding.

Detailed API reference for `@x402-avm/core/facilitator`, `@x402-avm/avm/exact/facilitator`, and `@x402-avm/extensions` packages.

This reference guide contains detailed information about AWS CloudFormation resources, intrinsic functions, and configurations for CloudFront CDN infrastructure.

Detailed API reference for the x402-avm Python package core components and AVM mechanism.

This skill includes detailed reference files for specific topics. Consult these when you need in-depth guidance.

| Storage | Scope | Who Pays MBR | Use Case | |---------|-------|--------------|----------| | `GlobalState` | App-wide | App account | Shared app data | | `LocalState` | Per-user | User (on opt-in) | Per-user data with opt-in | | `Box` | App-wide | App account | Large data, single key | | `BoxMap` | Per-key | App account | Per-user data without opt-in |

**Problem**: Using default isolation level when stronger guarantees needed.

Access group transactions using typed `gtxn` functions with `uint64` indices:

Create inner transactions and access group transactions in Algorand Python smart contracts.

Transactions should be managed at the **service layer**, not the store (repository) layer. The service layer knows which operations must be atomic. Individual store methods should not start their own transactions because:

| Type | Description | Constructor | |------|-------------|-------------| | `uint64` | 64-bit unsigned integer | `Uint64()` | | `bytes` | Byte array | `Bytes()` | | `bigint` | Up to 512-bit unsigned integer | `BigUInt` | | `string` | UTF-8 string | Native strings | | `bool` | Boolean | `true`/`false` |