Recently added agent tools.

A developer tool highlighting an issue with unclosed frontmatter syntax in skill files.

No Frontmatter Skill is a developer tool that identifies the absence of YAML frontmatter in a skill configuration.

Bad Skill is an incomplete AI agent tool missing essential fields such as name and description.

lark-demo is a demonstration skill designed for use with development tools to interact with APIs and messaging.

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An AI tool that automates the creation of targeted questionnaires to gather information from others in order to aid decision-making.

Compact the current conversation into a handoff document for another agent to pick up.

wait-what is an AI agent tool designed to request clarification and rephrase messages to ensure clear communication and understanding.

A tool designed to facilitate the structured writing and editing of agent-related documents and skills for AI agents, focusing on clarity, modularity, and efficient context handling.

An interactive, stateful workspace designed to teach users new skills or concepts through structured lessons, resources, and learning records.

A tool that automates setting up Husky pre-commit hooks with lint-staged, Prettier formatting, type checking, and tests in a code repository.

An AI tool that rigorously questions and evaluates plans or decisions by constructing and exploring a branching design tree of user decisions to achieve thorough understanding and stress-test thinking.

An AI tool designed to conduct rigorous interview-style sessions to refine plans or designs.

A developer tool for migrating TypeScript test files to use type-safe partial data assertions with @total-typescript/shoehorn instead of unsafe 'as' type assertions.

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.

An AI tool that organizes and shapes raw textual material into a structured article, paragraph by paragraph, facilitating content creation and presentation.

Wire dependency-cruiser into a TypeScript repo so each package is a deep module — implementation hidden in subfolders, reachable only through its entry-point files. User-invoked.

An AI tool that assists users in exploring and collecting unstructured writing fragments to aid creative writing and idea development.

A git safety tool that sets up hooks to block dangerous git commands before they execute, preventing destructive operations in code repositories.

Writing, exploit — assemble raw material into a journey of beats, grounding each term before a beat leans on it.

Plan a huge chunk of work — more than one agent session can hold — as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar third-party dashboard, or running a one-off migration or cutover. Don't invoke this for steps the agent can perform itself.

Hand the current conversation off to a fresh background agent that picks up the work immediately.

Grill me about specs for the workflows I want to build, within this workspace.

Move issues and external PRs through a state machine of triage roles — categorise, verify, grill if needed, and write agent-ready briefs.

Turn the current conversation into a spec and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker — edges as text in one file per ticket locally, or native blocking links on a real tracker.

Use when you need to resolve an in-progress git merge/rebase conflict.

Configure this repo for the engineering skills — set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.

Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.

Implement a piece of work based on a spec or set of tickets.

Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.

Ask which skill or flow fits your situation. A router over the skills in this repo.

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (us

Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deploy

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quo

Deploy Python (Flask/Django/FastAPI) code to Azure App Service Linux. WHEN: \"Flask App Service\", \"Django App Service\", \"FastAPI App Service\", \"deploy Python to App Service\". DO NOT USE FOR: Container Apps, Functions, non-Python, Terraform/Bicep/IaC, full infra — use azure-prepare.

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, agent CI/CD, optimize prompt, improve prompt,

An AI tool that guides developers through Microsoft Entra ID app registration, OAuth 2.0 authentication setup, and MSAL integration for secure Azure AD authentication in applications.

Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents),

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deploym

A developer tool for provisioning and managing Microsoft Entra Agent Identities with OAuth 2.0 token exchange using Microsoft Graph and SDKs.

Analyzes Azure resource groups to generate detailed architecture diagrams visualizing resource relationships and topology for infrastructure understanding.