copilot-sdk

Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.

6 stars

Best use case

copilot-sdk is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.

Teams using copilot-sdk should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/copilot-sdk/SKILL.md --create-dirs "https://raw.githubusercontent.com/Harmeet10000/skills/main/skills/frontend/copilot-sdk/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/copilot-sdk/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How copilot-sdk Compares

Feature / Agentcopilot-sdkStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# GitHub Copilot SDK

Embed Copilot's agentic workflows in any application using Python, TypeScript, Go, or .NET.

## Overview

The GitHub Copilot SDK exposes the same engine behind Copilot CLI: a production-tested agent runtime you can invoke programmatically. No need to build your own orchestration - you define agent behavior, Copilot handles planning, tool invocation, file edits, and more.

## Prerequisites

1. **GitHub Copilot CLI** installed and authenticated ([Installation guide](https://docs.github.com/en/copilot/how-tos/set-up/install-copilot-cli))
2. **Language runtime**: Node.js 18+, Python 3.8+, Go 1.21+, or .NET 8.0+

Verify CLI: `copilot --version`

## Installation

### Node.js/TypeScript
```bash
mkdir copilot-demo && cd copilot-demo
npm init -y --init-type module
npm install @github/copilot-sdk tsx
```

### Python
```bash
pip install github-copilot-sdk
```

### Go
```bash
mkdir copilot-demo && cd copilot-demo
go mod init copilot-demo
go get github.com/github/copilot-sdk/go
```

### .NET
```bash
dotnet new console -n CopilotDemo && cd CopilotDemo
dotnet add package GitHub.Copilot.SDK
```

## Quick Start

### TypeScript
```typescript
import { CopilotClient } from "@github/copilot-sdk";

const client = new CopilotClient();
const session = await client.createSession({ model: "gpt-4.1" });

const response = await session.sendAndWait({ prompt: "What is 2 + 2?" });
console.log(response?.data.content);

await client.stop();
process.exit(0);
```

Run: `npx tsx index.ts`

### Python
```python
import asyncio
from copilot import CopilotClient

async def main():
    client = CopilotClient()
    await client.start()

    session = await client.create_session({"model": "gpt-4.1"})
    response = await session.send_and_wait({"prompt": "What is 2 + 2?"})

    print(response.data.content)
    await client.stop()

asyncio.run(main())
```

### Go
```go
package main

import (
    "fmt"
    "log"
    "os"
    copilot "github.com/github/copilot-sdk/go"
)

func main() {
    client := copilot.NewClient(nil)
    if err := client.Start(); err != nil {
        log.Fatal(err)
    }
    defer client.Stop()

    session, err := client.CreateSession(&copilot.SessionConfig{Model: "gpt-4.1"})
    if err != nil {
        log.Fatal(err)
    }

    response, err := session.SendAndWait(copilot.MessageOptions{Prompt: "What is 2 + 2?"}, 0)
    if err != nil {
        log.Fatal(err)
    }

    fmt.Println(*response.Data.Content)
    os.Exit(0)
}
```

### .NET (C#)
```csharp
using GitHub.Copilot.SDK;

await using var client = new CopilotClient();
await using var session = await client.CreateSessionAsync(new SessionConfig { Model = "gpt-4.1" });

var response = await session.SendAndWaitAsync(new MessageOptions { Prompt = "What is 2 + 2?" });
Console.WriteLine(response?.Data.Content);
```

Run: `dotnet run`

## Streaming Responses

Enable real-time output for better UX:

### TypeScript
```typescript
import { CopilotClient, SessionEvent } from "@github/copilot-sdk";

const client = new CopilotClient();
const session = await client.createSession({
    model: "gpt-4.1",
    streaming: true,
});

session.on((event: SessionEvent) => {
    if (event.type === "assistant.message_delta") {
        process.stdout.write(event.data.deltaContent);
    }
    if (event.type === "session.idle") {
        console.log(); // New line when done
    }
});

await session.sendAndWait({ prompt: "Tell me a short joke" });

await client.stop();
process.exit(0);
```

### Python
```python
import asyncio
import sys
from copilot import CopilotClient
from copilot.generated.session_events import SessionEventType

async def main():
    client = CopilotClient()
    await client.start()

    session = await client.create_session({
        "model": "gpt-4.1",
        "streaming": True,
    })

    def handle_event(event):
        if event.type == SessionEventType.ASSISTANT_MESSAGE_DELTA:
            sys.stdout.write(event.data.delta_content)
            sys.stdout.flush()
        if event.type == SessionEventType.SESSION_IDLE:
            print()

    session.on(handle_event)
    await session.send_and_wait({"prompt": "Tell me a short joke"})
    await client.stop()

asyncio.run(main())
```

### Go
```go
session, err := client.CreateSession(&copilot.SessionConfig{
    Model:     "gpt-4.1",
    Streaming: true,
})

session.On(func(event copilot.SessionEvent) {
    if event.Type == "assistant.message_delta" {
        fmt.Print(*event.Data.DeltaContent)
    }
    if event.Type == "session.idle" {
        fmt.Println()
    }
})

_, err = session.SendAndWait(copilot.MessageOptions{Prompt: "Tell me a short joke"}, 0)
```

### .NET
```csharp
await using var session = await client.CreateSessionAsync(new SessionConfig
{
    Model = "gpt-4.1",
    Streaming = true,
});

session.On(ev =>
{
    if (ev is AssistantMessageDeltaEvent deltaEvent)
        Console.Write(deltaEvent.Data.DeltaContent);
    if (ev is SessionIdleEvent)
        Console.WriteLine();
});

await session.SendAndWaitAsync(new MessageOptions { Prompt = "Tell me a short joke" });
```

## Custom Tools

Define tools that Copilot can invoke during reasoning. When you define a tool, you tell Copilot:
1. **What the tool does** (description)
2. **What parameters it needs** (schema)
3. **What code to run** (handler)

### TypeScript (JSON Schema)
```typescript
import { CopilotClient, defineTool, SessionEvent } from "@github/copilot-sdk";

const getWeather = defineTool("get_weather", {
    description: "Get the current weather for a city",
    parameters: {
        type: "object",
        properties: {
            city: { type: "string", description: "The city name" },
        },
        required: ["city"],
    },
    handler: async (args: { city: string }) => {
        const { city } = args;
        // In a real app, call a weather API here
        const conditions = ["sunny", "cloudy", "rainy", "partly cloudy"];
        const temp = Math.floor(Math.random() * 30) + 50;
        const condition = conditions[Math.floor(Math.random() * conditions.length)];
        return { city, temperature: `${temp}°F`, condition };
    },
});

const client = new CopilotClient();
const session = await client.createSession({
    model: "gpt-4.1",
    streaming: true,
    tools: [getWeather],
});

session.on((event: SessionEvent) => {
    if (event.type === "assistant.message_delta") {
        process.stdout.write(event.data.deltaContent);
    }
});

await session.sendAndWait({
    prompt: "What's the weather like in Seattle and Tokyo?",
});

await client.stop();
process.exit(0);
```

### Python (Pydantic)
```python
import asyncio
import random
import sys
from copilot import CopilotClient
from copilot.tools import define_tool
from copilot.generated.session_events import SessionEventType
from pydantic import BaseModel, Field

class GetWeatherParams(BaseModel):
    city: str = Field(description="The name of the city to get weather for")

@define_tool(description="Get the current weather for a city")
async def get_weather(params: GetWeatherParams) -> dict:
    city = params.city
    conditions = ["sunny", "cloudy", "rainy", "partly cloudy"]
    temp = random.randint(50, 80)
    condition = random.choice(conditions)
    return {"city": city, "temperature": f"{temp}°F", "condition": condition}

async def main():
    client = CopilotClient()
    await client.start()

    session = await client.create_session({
        "model": "gpt-4.1",
        "streaming": True,
        "tools": [get_weather],
    })

    def handle_event(event):
        if event.type == SessionEventType.ASSISTANT_MESSAGE_DELTA:
            sys.stdout.write(event.data.delta_content)
            sys.stdout.flush()

    session.on(handle_event)

    await session.send_and_wait({
        "prompt": "What's the weather like in Seattle and Tokyo?"
    })

    await client.stop()

asyncio.run(main())
```

### Go
```go
type WeatherParams struct {
    City string `json:"city" jsonschema:"The city name"`
}

type WeatherResult struct {
    City        string `json:"city"`
    Temperature string `json:"temperature"`
    Condition   string `json:"condition"`
}

getWeather := copilot.DefineTool(
    "get_weather",
    "Get the current weather for a city",
    func(params WeatherParams, inv copilot.ToolInvocation) (WeatherResult, error) {
        conditions := []string{"sunny", "cloudy", "rainy", "partly cloudy"}
        temp := rand.Intn(30) + 50
        condition := conditions[rand.Intn(len(conditions))]
        return WeatherResult{
            City:        params.City,
            Temperature: fmt.Sprintf("%d°F", temp),
            Condition:   condition,
        }, nil
    },
)

session, _ := client.CreateSession(&copilot.SessionConfig{
    Model:     "gpt-4.1",
    Streaming: true,
    Tools:     []copilot.Tool{getWeather},
})
```

### .NET (Microsoft.Extensions.AI)
```csharp
using GitHub.Copilot.SDK;
using Microsoft.Extensions.AI;
using System.ComponentModel;

var getWeather = AIFunctionFactory.Create(
    ([Description("The city name")] string city) =>
    {
        var conditions = new[] { "sunny", "cloudy", "rainy", "partly cloudy" };
        var temp = Random.Shared.Next(50, 80);
        var condition = conditions[Random.Shared.Next(conditions.Length)];
        return new { city, temperature = $"{temp}°F", condition };
    },
    "get_weather",
    "Get the current weather for a city"
);

await using var session = await client.CreateSessionAsync(new SessionConfig
{
    Model = "gpt-4.1",
    Streaming = true,
    Tools = [getWeather],
});
```

## How Tools Work

When Copilot decides to call your tool:
1. Copilot sends a tool call request with the parameters
2. The SDK runs your handler function
3. The result is sent back to Copilot
4. Copilot incorporates the result into its response

Copilot decides when to call your tool based on the user's question and your tool's description.

## Interactive CLI Assistant

Build a complete interactive assistant:

### TypeScript
```typescript
import { CopilotClient, defineTool, SessionEvent } from "@github/copilot-sdk";
import * as readline from "readline";

const getWeather = defineTool("get_weather", {
    description: "Get the current weather for a city",
    parameters: {
        type: "object",
        properties: {
            city: { type: "string", description: "The city name" },
        },
        required: ["city"],
    },
    handler: async ({ city }) => {
        const conditions = ["sunny", "cloudy", "rainy", "partly cloudy"];
        const temp = Math.floor(Math.random() * 30) + 50;
        const condition = conditions[Math.floor(Math.random() * conditions.length)];
        return { city, temperature: `${temp}°F`, condition };
    },
});

const client = new CopilotClient();
const session = await client.createSession({
    model: "gpt-4.1",
    streaming: true,
    tools: [getWeather],
});

session.on((event: SessionEvent) => {
    if (event.type === "assistant.message_delta") {
        process.stdout.write(event.data.deltaContent);
    }
});

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
});

console.log("Weather Assistant (type 'exit' to quit)");
console.log("Try: 'What's the weather in Paris?'\n");

const prompt = () => {
    rl.question("You: ", async (input) => {
        if (input.toLowerCase() === "exit") {
            await client.stop();
            rl.close();
            return;
        }

        process.stdout.write("Assistant: ");
        await session.sendAndWait({ prompt: input });
        console.log("\n");
        prompt();
    });
};

prompt();
```

### Python
```python
import asyncio
import random
import sys
from copilot import CopilotClient
from copilot.tools import define_tool
from copilot.generated.session_events import SessionEventType
from pydantic import BaseModel, Field

class GetWeatherParams(BaseModel):
    city: str = Field(description="The name of the city to get weather for")

@define_tool(description="Get the current weather for a city")
async def get_weather(params: GetWeatherParams) -> dict:
    conditions = ["sunny", "cloudy", "rainy", "partly cloudy"]
    temp = random.randint(50, 80)
    condition = random.choice(conditions)
    return {"city": params.city, "temperature": f"{temp}°F", "condition": condition}

async def main():
    client = CopilotClient()
    await client.start()

    session = await client.create_session({
        "model": "gpt-4.1",
        "streaming": True,
        "tools": [get_weather],
    })

    def handle_event(event):
        if event.type == SessionEventType.ASSISTANT_MESSAGE_DELTA:
            sys.stdout.write(event.data.delta_content)
            sys.stdout.flush()

    session.on(handle_event)

    print("Weather Assistant (type 'exit' to quit)")
    print("Try: 'What's the weather in Paris?'\n")

    while True:
        try:
            user_input = input("You: ")
        except EOFError:
            break

        if user_input.lower() == "exit":
            break

        sys.stdout.write("Assistant: ")
        await session.send_and_wait({"prompt": user_input})
        print("\n")

    await client.stop()

asyncio.run(main())
```

## MCP Server Integration

Connect to MCP (Model Context Protocol) servers for pre-built tools. Connect to GitHub's MCP server for repository, issue, and PR access:

### TypeScript
```typescript
const session = await client.createSession({
    model: "gpt-4.1",
    mcpServers: {
        github: {
            type: "http",
            url: "https://api.githubcopilot.com/mcp/",
        },
    },
});
```

### Python
```python
session = await client.create_session({
    "model": "gpt-4.1",
    "mcp_servers": {
        "github": {
            "type": "http",
            "url": "https://api.githubcopilot.com/mcp/",
        },
    },
})
```

### Go
```go
session, _ := client.CreateSession(&copilot.SessionConfig{
    Model: "gpt-4.1",
    MCPServers: map[string]copilot.MCPServerConfig{
        "github": {
            Type: "http",
            URL:  "https://api.githubcopilot.com/mcp/",
        },
    },
})
```

### .NET
```csharp
await using var session = await client.CreateSessionAsync(new SessionConfig
{
    Model = "gpt-4.1",
    McpServers = new Dictionary<string, McpServerConfig>
    {
        ["github"] = new McpServerConfig
        {
            Type = "http",
            Url = "https://api.githubcopilot.com/mcp/",
        },
    },
});
```

## Custom Agents

Define specialized AI personas for specific tasks:

### TypeScript
```typescript
const session = await client.createSession({
    model: "gpt-4.1",
    customAgents: [{
        name: "pr-reviewer",
        displayName: "PR Reviewer",
        description: "Reviews pull requests for best practices",
        prompt: "You are an expert code reviewer. Focus on security, performance, and maintainability.",
    }],
});
```

### Python
```python
session = await client.create_session({
    "model": "gpt-4.1",
    "custom_agents": [{
        "name": "pr-reviewer",
        "display_name": "PR Reviewer",
        "description": "Reviews pull requests for best practices",
        "prompt": "You are an expert code reviewer. Focus on security, performance, and maintainability.",
    }],
})
```

## System Message

Customize the AI's behavior and personality:

### TypeScript
```typescript
const session = await client.createSession({
    model: "gpt-4.1",
    systemMessage: {
        content: "You are a helpful assistant for our engineering team. Always be concise.",
    },
});
```

### Python
```python
session = await client.create_session({
    "model": "gpt-4.1",
    "system_message": {
        "content": "You are a helpful assistant for our engineering team. Always be concise.",
    },
})
```

## External CLI Server

Run the CLI in server mode separately and connect the SDK to it. Useful for debugging, resource sharing, or custom environments.

### Start CLI in Server Mode
```bash
copilot --server --port 4321
```

### Connect SDK to External Server

#### TypeScript
```typescript
const client = new CopilotClient({
    cliUrl: "localhost:4321"
});

const session = await client.createSession({ model: "gpt-4.1" });
```

#### Python
```python
client = CopilotClient({
    "cli_url": "localhost:4321"
})
await client.start()

session = await client.create_session({"model": "gpt-4.1"})
```

#### Go
```go
client := copilot.NewClient(&copilot.ClientOptions{
    CLIUrl: "localhost:4321",
})

if err := client.Start(); err != nil {
    log.Fatal(err)
}

session, _ := client.CreateSession(&copilot.SessionConfig{Model: "gpt-4.1"})
```

#### .NET
```csharp
using var client = new CopilotClient(new CopilotClientOptions
{
    CliUrl = "localhost:4321"
});

await using var session = await client.CreateSessionAsync(new SessionConfig { Model = "gpt-4.1" });
```

**Note:** When `cliUrl` is provided, the SDK will not spawn or manage a CLI process - it only connects to the existing server.

## Event Types

| Event | Description |
|-------|-------------|
| `user.message` | User input added |
| `assistant.message` | Complete model response |
| `assistant.message_delta` | Streaming response chunk |
| `assistant.reasoning` | Model reasoning (model-dependent) |
| `assistant.reasoning_delta` | Streaming reasoning chunk |
| `tool.execution_start` | Tool invocation started |
| `tool.execution_complete` | Tool execution finished |
| `session.idle` | No active processing |
| `session.error` | Error occurred |

## Client Configuration

| Option | Description | Default |
|--------|-------------|---------|
| `cliPath` | Path to Copilot CLI executable | System PATH |
| `cliUrl` | Connect to existing server (e.g., "localhost:4321") | None |
| `port` | Server communication port | Random |
| `useStdio` | Use stdio transport instead of TCP | true |
| `logLevel` | Logging verbosity | "info" |
| `autoStart` | Launch server automatically | true |
| `autoRestart` | Restart on crashes | true |
| `cwd` | Working directory for CLI process | Inherited |

## Session Configuration

| Option | Description |
|--------|-------------|
| `model` | LLM to use ("gpt-4.1", "claude-sonnet-4.5", etc.) |
| `sessionId` | Custom session identifier |
| `tools` | Custom tool definitions |
| `mcpServers` | MCP server connections |
| `customAgents` | Custom agent personas |
| `systemMessage` | Override default system prompt |
| `streaming` | Enable incremental response chunks |
| `availableTools` | Whitelist of permitted tools |
| `excludedTools` | Blacklist of disabled tools |

## Session Persistence

Save and resume conversations across restarts:

### Create with Custom ID
```typescript
const session = await client.createSession({
    sessionId: "user-123-conversation",
    model: "gpt-4.1"
});
```

### Resume Session
```typescript
const session = await client.resumeSession("user-123-conversation");
await session.send({ prompt: "What did we discuss earlier?" });
```

### List and Delete Sessions
```typescript
const sessions = await client.listSessions();
await client.deleteSession("old-session-id");
```

## Error Handling

```typescript
try {
    const client = new CopilotClient();
    const session = await client.createSession({ model: "gpt-4.1" });
    const response = await session.sendAndWait(
        { prompt: "Hello!" },
        30000 // timeout in ms
    );
} catch (error) {
    if (error.code === "ENOENT") {
        console.error("Copilot CLI not installed");
    } else if (error.code === "ECONNREFUSED") {
        console.error("Cannot connect to Copilot server");
    } else {
        console.error("Error:", error.message);
    }
} finally {
    await client.stop();
}
```

## Graceful Shutdown

```typescript
process.on("SIGINT", async () => {
    console.log("Shutting down...");
    await client.stop();
    process.exit(0);
});
```

## Common Patterns

### Multi-turn Conversation
```typescript
const session = await client.createSession({ model: "gpt-4.1" });

await session.sendAndWait({ prompt: "My name is Alice" });
await session.sendAndWait({ prompt: "What's my name?" });
// Response: "Your name is Alice"
```

### File Attachments
```typescript
await session.send({
    prompt: "Analyze this file",
    attachments: [{
        type: "file",
        path: "./data.csv",
        displayName: "Sales Data"
    }]
});
```

### Abort Long Operations
```typescript
const timeoutId = setTimeout(() => {
    session.abort();
}, 60000);

session.on((event) => {
    if (event.type === "session.idle") {
        clearTimeout(timeoutId);
    }
});
```

## Available Models

Query available models at runtime:

```typescript
const models = await client.getModels();
// Returns: ["gpt-4.1", "gpt-4o", "claude-sonnet-4.5", ...]
```

## Best Practices

1. **Always cleanup**: Use `try-finally` or `defer` to ensure `client.stop()` is called
2. **Set timeouts**: Use `sendAndWait` with timeout for long operations
3. **Handle events**: Subscribe to error events for robust error handling
4. **Use streaming**: Enable streaming for better UX on long responses
5. **Persist sessions**: Use custom session IDs for multi-turn conversations
6. **Define clear tools**: Write descriptive tool names and descriptions

## Architecture

```
Your Application
       |
  SDK Client
       | JSON-RPC
  Copilot CLI (server mode)
       |
  GitHub (models, auth)
```

The SDK manages the CLI process lifecycle automatically. All communication happens via JSON-RPC over stdio or TCP.

## Resources

- **GitHub Repository**: https://github.com/github/copilot-sdk
- **Getting Started Tutorial**: https://github.com/github/copilot-sdk/blob/main/docs/tutorials/first-app.md
- **GitHub MCP Server**: https://github.com/github/github-mcp-server
- **MCP Servers Directory**: https://github.com/modelcontextprotocol/servers
- **Cookbook**: https://github.com/github/copilot-sdk/tree/main/cookbook
- **Samples**: https://github.com/github/copilot-sdk/tree/main/samples

## Status

This SDK is in **Technical Preview** and may have breaking changes. Not recommended for production use yet.

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6
from Harmeet10000/skills

Write, optimize, and grow Substack content — both newsletter issues (email-first) and web posts (web-first articles/essays). Covers ghostwriting with voice matching, Substack algorithm optimization, Notes strategy, email formatting, SEO, growth tactics, and monetization planning. Use when the user mentions Substack, newsletters, write a newsletter issue, Substack post, Substack article, web post on Substack, evergreen content, SEO for Substack, newsletter growth, Notes strategy, ghostwrite for, match someone's voice, write in the style of, newsletter monetization, paid subscribers, or any task involving Substack as a platform. Also trigger for general article/newsletter writing even if Substack isn't named explicitly, or when the user wants to adapt existing content (blog post, talk, thread) into newsletter or web post format. Do NOT use for generic blog post writing without a newsletter/Substack context (-> See samber/cc-skills@technical-article-writer skill).

press-release-writer

6
from Harmeet10000/skills

Write professional press releases for any occasion, media type, and country. Use when the user wants to write, draft, or improve a press release, communiqué de presse, media announcement, news release, or PR statement — including product launches, funding rounds, partnerships, crisis communications, earnings, executive hires, events, M&A, open source milestones, and media advisories. Covers all release types, media targets (print, digital/wire, broadcast, social/SMPR, trade press), and region-specific conventions (Western/Eastern Europe, Americas, Middle East, Africa, Asia, Oceania). Also trigger when the user says 'I need to announce something' or 'how do I tell the press about X.'

pdf

6
from Harmeet10000/skills

Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

linkedin-ghostwriting

6
from Harmeet10000/skills

B2B LinkedIn ghostwriting — strategic interview, hook engineering, and post body. Use when the user wants to write LinkedIn content, create ghostwritten posts, ghostwrite for a founder or executive, develop a B2B social strategy, or needs hooks, post structures, or copywriting frameworks for LinkedIn. Apply when the user shares a story, result, or insight and wants it turned into a post.

docx

6
from Harmeet10000/skills

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

documentation

6
from Harmeet10000/skills

Creates, structures, and reviews technical documentation following the Diátaxis framework (tutorials, how-to guides, reference, and explanation pages). Use when a user needs to write or reorganize docs, structure a tutorial vs. a how-to guide, build reference docs or API documentation, create explanation pages, choose between Diátaxis documentation types, or improve existing documentation structure. Trigger terms include: documentation structure, Diátaxis, tutorials vs how-to guides, organize docs, user guide, reference docs, technical writing.

doc-coauthoring

6
from Harmeet10000/skills

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.