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Everything your AI needs, in one place.
Ready-made agents, skills, personas, prompts, templates and tools. Each one is checked before it goes live, works with any model, and installs in a click. Rate what you use so the best rises to the top.
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A service that does a whole job for you - research, coding, support - and reports back.
Step-by-step instructions an AI follows for one kind of task. Install once, reuse everywhere.
A voice and set of rules layered onto any model: tone, audience, do's and don'ts.
A ready-to-use prompt with fill-in-the-blank variables and notes on when it works best.
A complete routing setup - models, rules and settings - in one file you can apply in a minute.
A single function an AI can call: a calculator, a search, a database lookup.
A language model endpoint with its price, speed and quality declared so the router can compare it.
qe-test-idea-rewriting
Transform passive 'Verify X' test descriptions into active, observable test actions. Use when test ideas lack specificity, use vague language, or fail quality validation. Converts to action-verb forma
qe-verification-quality
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
dotnet-exception-handling
Comprehensive .NET exception handling quality improvement workflow. Auto-detects .NET projects, investigates 10 common exception handling mistakes, generates prioritized findings, and orchestrates fix
assess
Assesses and rates quality 0-10 across multiple dimensions (correctness, maintainability, security, performance, testability, simplicity) with pros/cons analysis. Compares against project conventions
code-review-playbook
Structured review processes, conventional comments, language-specific checklists, and feedback templates. Use when reviewing PRs, conducting code review, or standardizing review practice.
golden-dataset
Golden dataset lifecycle patterns for curation, versioning, quality validation, and CI integration. Use when building evaluation datasets, managing dataset versions, validating quality scores, or inte
quality-gates
Use when assessing task complexity, before starting complex tasks, when stuck after multiple attempts, or reviewing code against best practices. Provides quality-gates scoring (1-5), escalation workfl
review-pr
PR review using parallel specialized agents for code quality, security, testing, architecture, and performance analysis. Synthesizes findings into a review report with conventional comments (praise/is
verify
Grade work that already exists and decide whether it can merge. Runs the project's current unit, integration, and E2E suites plus security scanning and type checking, scores every dimension 0-10, and
agent-evaluation
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evi
pipeline-evaluator
Evaluates completed agent pipelines across 5 scoring dimensions and produces a composite verdict with actionable recommendations
plan-quality-verifier
Verifies implementation plan quality across 8 dimensions (requirement-coverage, task-completeness, dependency-validity, scope-sanity, artifact-wiring, risk-assessment, testability, estimation-quality)
memory-audit
Comprehensive memory quality review across 6 dimensions: purity, freshness, coverage, clarity, relevance, and structure. Generates prioritized findings with specific memory references and actionable r
code-review-playbook
Use this skill when conducting or improving code reviews. Provides structured review processes, conventional comments patterns, language-specific checklists, and feedback templates. Ensures consistent
testing-strategy
Comprehensive testing strategy using Vitest for unit/integration tests and Playwright for E2E tests with best practices and coverage targets
quick-quality-check
Lightning-fast quality check using parallel command execution. Runs theater detection, linting, security scan, and basic tests in parallel for instant feedback on code quality.
verification-quality-assurance
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
code-review
Code review assistance with linting, style checking, and best practices
skill-validator
Validate Agent Skills against the specification. Checks SKILL.md format, frontmatter fields, naming conventions, and directory structure.
code-review
代码审查和质量分析技能。用于审查代码、发现潜在问题、提供改进建议。当用户请求代码审查、代码质量分析或最佳实践建议时使用。
code-review-checklist
Guide an AI agent through a structured code review — correctness, security, performance, readability, and test coverage — producing a summary with actionable, prioritized feedback. Triggers on pull-re
tdd-workflow
Test-driven development workflow with comprehensive coverage requirements including unit, integration, and E2E tests
organvm-governance-pack
Curated bundle of governance and quality skills for ORGANVM ecosystem management. Includes ecosystem autopsy and discovery, promotion readiness, onboarding flows, stranger testing, repository standard
code-review-checklist
Generate context-aware code review checklists from PR diffs — tailored to language, codebase patterns, and team standards. Identifies what reviewers should focus on. NOT for automated code fixing, tes
Find
Search or browse by kind. Every card shows who made it, how many people installed it and what they think.
Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
Rate and publish
Leave a star rating after you have used it. Made something useful? Publish it - free listings go live immediately.
Prefer the terminal? osr stack apply registry://starter installs the starter template.