MCP Development
coollabsio/coolify
A skill your agent uses for Laravel MCP development. An agent skill from coollabsio/coolify.
Agent skill
by microsoft-foundry in microsoft-foundry/foundry-agent-webapp
Provides SSE streaming patterns for the chat API and frontend.
$ npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microsoft-foundry/foundry-agent-webapp implementing-chat-streaming --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/microsoft-foundry/foundry-agent-webapp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/implementing-chat-streaming .claude/skills/implementing-chat-streaming && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "implementing-chat-streaming" agent skill from https://github.com/microsoft-foundry/foundry-agent-webapp/tree/main/.github/skills/implementing-chat-streaming into .claude/skills/implementing-chat-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-chat-streaming", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/microsoft-foundry/foundry-agent-webapp/tree/main/.github/skills/implementing-chat-streamingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microsoft-foundry/foundry-agent-webapp implementing-chat-streaming --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft-foundry/foundry-agent-webapp.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/skills/implementing-chat-streaming .agents/skills/implementing-chat-streaming && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "implementing-chat-streaming" agent skill from https://github.com/microsoft-foundry/foundry-agent-webapp/tree/main/.github/skills/implementing-chat-streaming into .agents/skills/implementing-chat-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-chat-streaming", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microsoft-foundry/foundry-agent-webapp implementing-chat-streaming --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft-foundry/foundry-agent-webapp.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/skills/implementing-chat-streaming .cursor/skills/implementing-chat-streaming && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "implementing-chat-streaming" agent skill from https://github.com/microsoft-foundry/foundry-agent-webapp/tree/main/.github/skills/implementing-chat-streaming into .cursor/skills/implementing-chat-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-chat-streaming", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/microsoft-foundry/foundry-agent-webapp.git --path .github/skills/implementing-chat-streaming--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microsoft-foundry/foundry-agent-webapp implementing-chat-streaming --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft-foundry/foundry-agent-webapp.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/skills/implementing-chat-streaming .gemini/skills/implementing-chat-streaming && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "implementing-chat-streaming" agent skill from https://github.com/microsoft-foundry/foundry-agent-webapp/tree/main/.github/skills/implementing-chat-streaming into .gemini/skills/implementing-chat-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-chat-streaming", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install microsoft-foundry/foundry-agent-webapp implementing-chat-streamingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microsoft-foundry/foundry-agent-webapp.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/skills/implementing-chat-streaming .github/skills/implementing-chat-streaming && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "implementing-chat-streaming" agent skill from https://github.com/microsoft-foundry/foundry-agent-webapp/tree/main/.github/skills/implementing-chat-streaming into .github/skills/implementing-chat-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-chat-streaming", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microsoft-foundry/foundry-agent-webapp implementing-chat-streaming --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft-foundry/foundry-agent-webapp.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/skills/implementing-chat-streaming .opencode/skills/implementing-chat-streaming && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "implementing-chat-streaming" agent skill from https://github.com/microsoft-foundry/foundry-agent-webapp/tree/main/.github/skills/implementing-chat-streaming into .opencode/skills/implementing-chat-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-chat-streaming", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
implementing-chat-streamingProvides SSE streaming patterns for the chat API and frontend.
Implementing Chat Streaming is an agent skill from microsoft-foundry/foundry-agent-webapp. Provides SSE streaming patterns for the chat API and frontend. Use when implementing or modifying chat streaming, handling SSE events, or troubleshooting message flow between frontend and backend.
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Frontend & Design. The repository describes itself as: GitHub Copilot enabled repo for building and deploying a web application with Entra ID authentication and integrated with Azure AI Foundry Agents. The licence is MIT.
Read from SKILL.md and the folder at commit f6cb362. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are csharp).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Implementing Chat Streaming loads about 1.9k tokens when it runs. Until then it costs about 56 tokens; SKILL.md has 269 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from microsoft-foundry/foundry-agent-webapp at commit f6cb362, republished under its MIT licence (© microsoft-foundry). 269 words, ~1,861 tokens.
.claude/skills/implementing-chat-streaming/SKILL.md (or your agent's skills folder).app.MapPost("/api/chat/stream", async (
ChatRequest request,
AgentFrameworkService agentService,
HttpContext httpContext,
CancellationToken cancellationToken) =>
{
httpContext.Response.Headers.Append("Content-Type", "text/event-stream");
httpContext.Response.Headers.Append("Cache-Control", "no-cache");
var conversationId = request.ConversationId
?? await agentService.CreateConversationAsync(request.Message, cancellationToken);
// Send conversation ID first
await httpContext.Response.WriteAsync(
$"data: {{\"type\":\"conversationId\",\"conversationId\":\"{conversationId}\"}}\n\n",
cancellationToken);
await httpContext.Response.Body.FlushAsync(cancellationToken);
// Stream chunks
await foreach (var chunk in agentService.StreamMessageAsync(
conversationId, request.Message, request.ImageDataUris, cancellationToken))
{
var json = JsonSerializer.Serialize(new { type = "chunk", content = chunk });
await httpContext.Response.WriteAsync($"data: {json}\n\n", cancellationToken);
await httpContext.Response.Body.FlushAsync(cancellationToken);
}
await httpContext.Response.WriteAsync("data: {\"type\":\"done\"}\n\n", cancellationToken);
})
.RequireAuthorization("RequireChatScope");Actual return type: IAsyncEnumerable<StreamChunk> (not raw strings)
Why direct SDK? Uses ProjectResponsesClient directly because we need typed access to MCP approvals, file search quotes, and citation annotations. See .github/skills/researching-azure-ai-sdk/SKILL.md for full rationale.
public async IAsyncEnumerable<StreamChunk> StreamMessageAsync(
string conversationId,
string message,
List<string>? imageDataUris = null,
[EnumeratorCancellation] CancellationToken cancellationToken = default)
{
ObjectDisposedException.ThrowIf(_disposed, this);
// Stream response - yields StreamChunk with text deltas OR annotations
await foreach (var update in responsesClient.CreateResponseStreamingAsync(...))
{
if (update is StreamingResponseOutputTextDeltaUpdate deltaUpdate)
{
yield return StreamChunk.Text(deltaUpdate.Delta);
}
else if (update is StreamingResponseOutputItemDoneUpdate itemDoneUpdate)
{
var annotations = ExtractAnnotations(itemDoneUpdate.Item, fileSearchQuotes);
if (annotations.Count > 0)
{
yield return StreamChunk.WithAnnotations(annotations);
}
}
}
}StreamChunk model (backend/WebApp.Api/Models/StreamChunk.cs):
IsText / TextDelta - Text contentHasAnnotations / Annotations - Citation metadataCHAT_SEND_MESSAGE
→ CHAT_ADD_ASSISTANT_MESSAGE
→ CHAT_START_STREAM
→ (repeat CHAT_STREAM_CHUNK)
→ CHAT_STREAM_ANNOTATIONS (optional, for citations)
→ CHAT_STREAM_COMPLETE (with usage metrics)If user cancels: CHAT_CANCEL_STREAM sets status to idle.
See: frontend/src/services/ChatService.ts
Key patterns:
data: linesBackend limits (see AzureAIAgentService.cs):
image/png, image/jpeg, image/gif, image/webpFrontend limits (see frontend/src/utils/fileAttachments.ts):
app.MapPost("/api/chat/stream", async (
ChatRequest request,
AgentFrameworkService agentService,
HttpContext httpContext,
IHostEnvironment env,
CancellationToken cancellationToken) =>
{
httpContext.Response.Headers.Append("Content-Type", "text/event-stream");
httpContext.Response.Headers.Append("Cache-Control", "no-cache");
var conversationId = request.ConversationId
?? await agentService.CreateConversationAsync(request.Message, cancellationToken);
await httpContext.Response.WriteAsync(
$"data: {{\"type\":\"conversationId\",\"conversationId\":\"{conversationId}\"}}\n\n",
cancellationToken);
await httpContext.Response.Body.FlushAsync(cancellationToken);
await foreach (var chunk in agentService.StreamMessageAsync(
conversationId, request.Message, request.ImageDataUris, cancellationToken))
{
var json = System.Text.Json.JsonSerializer.Serialize(new { type = "chunk", content = chunk });
await httpContext.Response.WriteAsync($"data: {json}\n\n", cancellationToken);
await httpContext.Response.Body.FlushAsync(cancellationToken);
}
await httpContext.Response.WriteAsync("data: {\"type\":\"done\"}\n\n", cancellationToken);
})
.RequireAuthorization("RequireChatScope")
.WithName("StreamChatMessage");See: backend/WebApp.Api/Services/AgentFrameworkService.cs
Key patterns in StreamMessageAsync:
IAsyncEnumerable<StreamChunk> with [EnumeratorCancellation]StreamingResponseOutputTextDeltaUpdate for text contentStreamingResponseOutputItemDoneUpdate for annotationsFileSearchCallResponseItem for citation contextStreamingResponseCompletedUpdateCHAT_SEND_MESSAGE
→ CHAT_ADD_ASSISTANT_MESSAGE
→ CHAT_START_STREAM
→ (repeat CHAT_STREAM_CHUNK)
→ CHAT_STREAM_ANNOTATIONS (optional, for citations)
→ CHAT_STREAM_COMPLETE (with usage: promptTokens, completionTokens, totalTokens, duration)Cancel: CHAT_CANCEL_STREAM sets status to idle and re-enables input.
Error: CHAT_ERROR with AppError containing message, optional retry action, timestamp.
| Event Type | Payload | Description |
|---|---|---|
conversationId | { conversationId: string } | Sent first for new conversations |
chunk | { content: string } | Text delta from agent response |
annotations | { annotations: [...] } | Citations (uri_citation, file_citation, etc.) |
usage | { duration, promptTokens, completionTokens, totalTokens } | Token metrics |
done | {} | Stream complete |
error | { message: string } | Error occurred |
Each state change prints (dev only):
🔄 [HH:MM:SS] ACTION_TYPE
Action: { … }
Changes: { field: before → after }© microsoft-foundry, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .github/skills/implementing-chat-streaming of microsoft-foundry/foundry-agent-webapp.
Open the folder on GitHubat commit f6cb362
Implementing Chat Streaming next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Implementing Chat Streaming this skillmicrosoft-foundry/foundry-agent-webapp | 127 | — | ~1.9k | Automated safety check: Pass | MIT | |
| MCP Developmentcoollabsio/coolify | 63k | 1 repos | ~949 | Automated safety check: Pass | MIT | |
| Turnstile Spincloudflare/skills | 3k | 4 repos | ~7.2k | Automated safety check: Notes | Apache-2.0 | |
| Paperclip Pagepaperclipai/paperclip | 98k | — | ~1k | Automated safety check: Pass | MIT | |
| Go HTML Views with Gomponentsmaragudk/gomponents | 1.9k | — | ~3.6k | Automated safety check: Pass | MIT | |
| Pinmeglitternetwork/pinme | 3.7k | — | ~3.8k | Automated safety check: Notes | MIT |
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microsoft-foundry/foundry-agent-webapp
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microsoft-foundry/foundry-agent-webapp
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microsoft-foundry/foundry-agent-webapp
Synchronize MCP server configuration between VS Code (.vscode/mcp.json) and Copilot CLI (~/.copilot/mcp-config.json).
microsoft-foundry/foundry-agent-webapp
Validate that Copilot CLI can see all repo skills, MCP servers, and custom instructions.
Categories
Provides SSE streaming patterns for the chat API and frontend. Implementing Chat Streaming is an agent skill from microsoft-foundry/foundry-agent-webapp. Provides SSE streaming patterns for the chat API and frontend.
Implementing Chat Streaming fits situations like: modifying chat streaming; handling SSE events; troubleshooting message flow between frontend and backend.
Run `npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a claude-code`. Or copy the skill folder (.github/skills/implementing-chat-streaming in microsoft-foundry/foundry-agent-webapp) into .claude/skills/implementing-chat-streaming in your project. Claude Code loads it when a task matches its description.
Run `npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a codex`. Or copy the skill folder (.github/skills/implementing-chat-streaming in microsoft-foundry/foundry-agent-webapp) into .agents/skills/implementing-chat-streaming in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft-foundry/foundry-agent-webapp --skill implementing-chat-streaming -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-chat-streaming, .gemini/skills/implementing-chat-streaming, .github/skills/implementing-chat-streaming and .opencode/skills/implementing-chat-streaming in your project.
SKILL.md names no scripts, command-line tools or credentials: Implementing Chat Streaming is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Implementing Chat Streaming is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Implementing Chat Streaming: MCP Development (coollabsio/coolify, 63k stars), Turnstile Spin (cloudflare/skills, 3k stars), Paperclip Page (paperclipai/paperclip, 98k stars) and Go HTML Views with Gomponents (maragudk/gomponents, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
microsoft-foundry (a GitHub organization) maintains it in microsoft-foundry/foundry-agent-webapp, which has 127 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on April 21, 2026.
Source: microsoft-foundry/foundry-agent-webapp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.