Artificial Intelligence skills

init

Generate or update chat customization files for AI coding agents

AI Agents

create-prompt

Create a reusable prompt file (.prompt.md) for a common task.

AI Agents

create-hook

Create a hook (.json) to enforce policy or automate agent lifecycle events.

AI Agents

create-agent

Create a custom agent (.agent.md) for a specific job.

AI Agents

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting session data.

AI Agents

agent-customization

**WORKFLOW SKILL** — Create, update, review, fix, or debug VS Code agent customization files (.instructions.md, .prompt.md, .agent.md, SKILL.md, copilot-instructions.md, AGENTS.md). USE FOR: saving coding preferences; troubleshooting why instructions/skills/agents are ignored or not invoked; configuring applyTo patterns; defining tool restrictions; creating custom agent modes or specialized workflows; packaging domain knowledge; fixing YAML frontmatter syntax. DO NOT USE FOR: general coding questions (use default agent); runtime debugging or error diagnosis; MCP server configuration (use MCP d

AI Agents

launch

Launch and automate VS Code Insiders with the Copilot Chat extension using @playwright/cli via Chrome DevTools Protocol. Use when you need to interact with the VS Code UI, automate the chat panel, test the extension UI, or take screenshots. Triggers include 'automate VS Code', 'interact with chat', 'test the UI', 'take a screenshot', 'launch with debugging'.

AI Agents

github-copilot-upgrader

Use this to update the Github Copilot CLI/SDK

AI Agents

vscode-dev-workbench

Use when the user wants to run the vscode.dev server locally and exercise the VS Code workbench or Agents window in the integrated browser against the local `microsoft/vscode` sources. Covers starting the dev server, the `vscode-quality=dev` URL, browser-driven interaction patterns, and optionally wiring up a local mock agent host for the Agents window.

AI Agents

sweeper-fix

Implement a VS Code Sweeper fix spec — fetch the sweeper's agent-fixable review record from its public state repo, implement the narrow fix in the current vscode checkout, and — after showing the diff — open a draft PR. Use ONLY when the request explicitly asks for the sweeper — "sweeper-fix", "sweeper", "vscodesweeper", a sweeper record, or a sweeper fix spec. Do NOT use for a plain "fix this issue" request that doesn't mention the sweeper; fix those directly with your normal tools instead.

AI Agents

sessions

Core principles and workflow router for changes to the Agents Window under src/vs/sessions.

AI Agents

policy-and-managed-settings

Use whenever adding, modifying, or reviewing any Copilot, agent, LLM, AI, tool, permission, sandbox, MCP, model, telemetry, feature-gate, setting, configuration, or enterprise control—especially anything an organization or administrator may need to manage. Start here to decide whether it belongs in runtime managed settings, a typed SDK contract, VS Code configuration policy, extension policy, or a split implementation. Run on every new Copilot/agent/LLM control and ANY change that adds a `policy:` field.

AI Agents

customizations-in-the-agent-host

Architecture and hard-won debugging lessons for customization enablement (plugins, MCP servers, agents, skills, instructions) in the agent host. Use when changing how customizations are discovered, published, enabled/disabled, or handed to a provider SDK; when a customization shows the wrong enabled state in the UI; or when a disabled MCP server or plugin is still reaching the model.

AI Agents

code-oss-logs

Find and read timestamped process logs from Code OSS dev builds, including main.log, renderer.log, extension host logs, and agenthost.log. For bundles produced by Export Agent Host Debug Logs, use agent-host-logs.

AI Agents

chat-customizations-editor

Use when working on the Chat Customizations editor — the management UI for agents, skills, instructions, hooks, prompts, MCP servers, and plugins.

AI Agents

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

AI Agents

agent-host-logs

Analyze Agent Host debug log exports. Use when given an ah-logs or ahp-logs zip/folder, an Export Agent Host Debug Logs bundle, events.jsonl, AHP JSONL transport logs, Agent Host.log, remote-agenthost.log, or copilot-logs.

AI Agents

agent-host-e2e-tests

Use when writing, recording, updating, validating, or troubleshooting the agent host end-to-end tests under src/vs/platform/agentHost/test/node/e2e (black-box tests that drive the whole agent host over the AHP protocol, using a CapiReplayProxy record/replay system for Claude/Copilot/Codex). Covers adding a cross-provider test, re-recording fixtures after an SDK bump, cross-platform Azure validation, gating non-deterministic or platform-specific tests, and diagnosing replay cache misses.

AI Agents

agent-host-chat-contributions

Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.

AI Agents

review-plan

Review an implementation plan produced by the Plan agent. It is CRITICAL to review plans before handing off to implementation — plans often have gaps, incorrect assumptions, or suboptimal sequencing that are cheaper to catch now than after coding. Use when the user asks to 'review the plan', 'check my plan', 'is this plan ready', or after the Plan agent produces a plan.md.

AI Agents

monitor-pr

Monitor a pull request until CI status or Copilot review is available. Use when: monitor PR, watch PR, land PR, wait for CI, wait for checks, wait for review, check PR status. Starts two async terminal tasks (CI + Copilot review) and reacts when either completes.

AI Agents

goal

Set, inspect, or control a durable goal — the agent keeps iterating across turns until the stop condition is met.

AI Agents

follow-goal

Give the agent a durable objective with a verifiable stopping condition, then keep iterating across turns until that condition is met. Use when the user says 'set a goal', 'follow a goal', '/goal …', 'keep working until …', or asks for a long-running task with a clear end state (migrations, large refactors, retry-until-green loops, experiments).

AI Agents