Skills

skills/
└── langgraph-docs/
    └── SKILL.md

---
name: langgraph-docs
description: Use this skill for requests related to LangGraph in order to fetch relevant documentation to provide accurate, up-to-date guidance.
---

# langgraph-docs

## Overview

This skill explains how to access LangGraph documentation to help answer questions and guide implementation.

## Instructions

### 1. Fetch the documentation index

Use the fetch_url tool to read the following URL:
https://docs.langchain.com/llms.txt

This provides a structured list of all available documentation with descriptions.

### 2. Select relevant documentation

Based on the question, identify 2-4 most relevant documentation URLs from the index. Prioritize:

- Specific how-to guides for implementation questions
- Core concept pages for understanding questions
- Tutorials for end-to-end examples
- Reference docs for API details

### 3. Fetch and synthesize

Use the fetch_url tool to read the selected documentation URLs, then answer the user's question. Give a direct answer first, include the minimum necessary context, and link to the source pages rather than quoting long passages.

import { createDeepAgent, FilesystemBackend } from "deepagents";

const backend = new FilesystemBackend({ rootDir: process.cwd() });

const agent = await createDeepAgent({
  model: "anthropic:claude-sonnet-4-6",
  backend,
  skills: ["/skills/"],
});

const result = await agent.invoke(
  { messages: [{ role: "user", content: "What is LangGraph?" }] },
  { configurable: { thread_id: "1" } },
);

# Good: specific about what and when
description: >-
  Extract text and tables from PDF files, fill PDF forms, and merge
  multiple PDFs. Use when working with PDF documents or when the user
  mentions PDFs, forms, or document extraction.

# Poor: too vague for reliable matching
description: Helps with PDFs.

skills/
└── data-pipeline/
    ├── SKILL.md
    └── references/
        ├── schema-reference.md
        └── error-codes.md

import { createDeepAgent } from "deepagents";

const SKILLS_BY_ROLE: Record<string, string[]> = {
  engineering: ["/skills/code-review/", "/skills/testing/", "/skills/deployment/"],
  data: ["/skills/sql-analysis/", "/skills/visualization/", "/skills/data-pipeline/"],
  support: ["/skills/ticket-triage/", "/skills/runbook/"],
};

function createAgentForUser(userRole: string) {
  return createDeepAgent({
    model: "anthropic:claude-sonnet-4-6",
    skills: SKILLS_BY_ROLE[userRole] ?? [],
  });
}

import {
  createDeepAgent,
  CompositeBackend,
  StateBackend,
  StoreBackend,
} from "deepagents";

const agent = await createDeepAgent({
  model: "anthropic:claude-sonnet-4-6",
  skills: ["/skills/"],
  backend: new CompositeBackend({
    default: new StateBackend(),
    routes: {
      "/skills/": new StoreBackend({
        namespace: (ctx) => [
          ctx.assistantId ?? "default",
          ctx.config?.configurable?.user_id ?? "anonymous",
        ],
      }),
    },
  }),
});

const researchSubagent = {
  name: "researcher",
  description: "Research assistant with specialized skills",
  systemPrompt: "You are a researcher.",
  tools: [webSearch],
  skills: ["/skills/research/", "/skills/web-search/"],  // Subagent-specific skills
};

const agent = await createDeepAgent({
  model: "google_genai:gemini-3.5-flash",
  skills: ["/skills/main/"],  // Main agent and GP subagent get these
  subagents: [researchSubagent],  // Researcher gets only its own skills
});

skills/
└── arxiv-search/
    ├── SKILL.md
    └── scripts/
        └── search.ts

---
name: arxiv-search
description: Search the arXiv preprint repository for research papers. Use when the user asks about academic papers, recent research, or scientific literature.
---

# arxiv-search

Search arXiv for papers matching the user's query.

## Instructions

1. Run `scripts/search.ts` with the user's query as an argument.
2. Parse the results and present them with title, authors, abstract summary, and link.
3. If the user asks for more detail on a specific paper, fetch the full abstract.

skills/
`-- order-helpers/
    |-- SKILL.md
    `-- scripts/
        `-- index.ts

---
name: order-helpers
description: Helper functions for normalizing and grouping order records.
metadata:
  entrypoint: scripts/index.ts
---

# order-helpers

Use this skill when order records need deterministic cleanup or aggregation.

Import these utilities into the REPL in order to interact with order data:

```typescript
const { groupByStatus } = await import("@/skills/order-helpers");
groupByStatus(...);
```

// skills/order-helpers/scripts/index.ts
interface Order {
  id: string;
  status: string;
}

export function groupByStatus(orders: Order[]) {
  return orders.reduce((acc, order) => {
    acc[order.status] = acc[order.status] ?? [];
    acc[order.status].push(order);
    return acc;
  }, {});
}

import { createDeepAgent, StateBackend } from "deepagents";
import { createCodeInterpreterMiddleware } from "@langchain/quickjs";

const backend = new StateBackend();

const agent = createDeepAgent({
  model: "openai:gpt-5.4",
  backend,
  skills: ["/skills/"],
  middleware: [createCodeInterpreterMiddleware({ skillsBackend: backend })],
});

const { groupByStatus } = await import("@/skills/order-helpers");

const grouped = groupByStatus(orders);
grouped;