SKILL RADAR · GITHUB
Useful agent skills, ranked by real adoption.
Browse verified skills from public repositories. Compare what each skill does, package contents, install activity, and source evidence before adding it to your agent.
- CATALOG SCOPE
- VERIFIED
- skills
- 5,771
- repositories
- 824
- last synced
- Sep 8, 2026
googleworkspacerecipe-create-presentation
Create a new Google Slides presentation and add initial slides.
- installs
- 2
- GitHub stars
- 30.7K
- Updated
- Aug 25
hkudscli-anything-notebooklm
Experimental NotebookLM harness for listing notebooks, managing sources, asking questions, generating artifacts, and downloading outputs through an installed notebooklm CLI.
- installs
- 2
- GitHub stars
- 48.9K
- Updated
- Aug 21
sickn33clean-code
This skill embodies the principles of \"Clean Code\" by Robert C. Martin (Uncle Bob). Use it to transform \"code that works\" into \"code that is clean.\"
- installs
- 2
- GitHub stars
- 45.9K
- Updated
- Sep 2
karpathyread-arxiv-paper
Use this skill when asked to read an arxiv paper given an arxiv URL
- installs
- 2
- GitHub stars
- 57.7K
- Updated
- Aug 2
jackweneropencli-browser
Use when an agent needs to drive a real Chrome window via opencli — inspect a page, fill forms, click through logged-in flows, or extract data ad-hoc. Covers the selector-first target contract, compound form fields, stale-ref handling, network capture, and the agent-native envelopes the CLI returns. Not for writing adapters — see opencli-adapter-author for that.
- installs
- 2
- GitHub stars
- 28.9K
- Updated
- Aug 30
wshobsonaccessibility-compliance
Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonai-debt-detector
- Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonbazel-build-optimization
Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonbefore-you-build
Pre-build product and feature risk review for founders, product managers, and AI-assisted builders. Use this skill when the user is about to build a landing page, MVP, SaaS product, internal tool, agent workflow, or major feature and needs to check demand, positioning, monetization, retention, trust, distribution, and adoption risk before implementation starts.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonbinary-analysis-patterns
Master binary analysis patterns including disassembly, decompilation, control flow analysis, and code pattern recognition. Use when analyzing executables, understanding compiled code, or performing static analysis on binaries.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonchangelog-automation
Automate changelog generation from commits, PRs, and releases following Keep a Changelog format. Use when setting up release workflows, generating release notes, or standardizing commit conventions.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsoncqrs-implementation
Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsondataset-curation
Prepare, format, and validate datasets for supervised fine-tuning and preference training. Use when converting raw data into training format, applying chat templates, configuring sequence packing, generating synthetic training data, or writing a dataset card before a run.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsondbt-transformation-patterns
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsondebugging-strategies
Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonembedding-strategies
Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonemployment-contract-templates
Create employment contracts, offer letters, and HR policy documents following legal best practices. Use when drafting employment agreements, creating HR policies, or standardizing employment documentation.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonevaluation-methodology
PluginEval quality methodology — dimensions, rubrics, statistical methods, and scoring formulas. Use this skill when understanding how plugin quality is measured, when interpreting a low score on a specific dimension, when deciding how to improve a skill's triggering accuracy or orchestration fitness, when calibrating scoring thresholds for your marketplace, or when explaining quality badges to external partners like Neon.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonfinetuning-method-selection
Decide whether to fine-tune at all, and route to the right method (SFT, DPO/ORPO/KTO, GRPO/RLVR, continued pretraining) and base model. Use when starting any fine-tuning effort, when unsure whether RAG or prompting would suffice, or when choosing between preference-optimization and reinforcement methods.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsongrounded-vault
Use when maintaining a durable Markdown knowledge store that agents compile from sources, when every number or quote in a wiki page must trace back to an immutable source, or when compiled pages need cheap drift detection against the code they describe. Teaches the raw/wiki/archive layout, per-claim provenance links, and git fingerprints for zero-token staleness checks.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonhads
Use when writing technical documentation that needs to be readable by both humans and AI models, converting existing docs to HADS format, validating a HADS document, or optimizing documentation for token-efficient AI consumption.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonhybrid-cloud-networking
Configure secure, high-performance connectivity between on-premises infrastructure and cloud platforms using VPN and dedicated connections. Use when building hybrid cloud architectures, connecting data centers to cloud, or implementing secure cross-premises networking.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonhybrid-search-implementation
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1
wshobsonincident-runbook-templates
Create structured incident response runbooks with step-by-step procedures, escalation paths, and recovery actions. Use this skill when building a service outage runbook for a payment processing system; creating database incident procedures covering connection pool exhaustion, replication lag, and disk space alerts; onboarding new on-call engineers who need step-by-step recovery guides written for a 3 AM brain; or standardizing escalation matrices across multiple engineering teams.
- installs
- 2
- GitHub stars
- 39.4K
- Updated
- Sep 1