# How the `resolve-library-id` Tool Selects the Best Library Match in Context7

> Learn how resolve-library-id selects the best library match by delegating to the Context7 API, which ranks candidates by relevance to your query and returns the top result first.

- Repository: [Upstash/context7](https://github.com/upstash/context7)
- Tags: how-to-guide
- Published: 2026-02-16

---

**The `resolve-library-id` tool delegates library selection to the Context7 API, which ranks candidates by relevance to the user's original query and returns the best match first.**

The `resolve-library-id` tool is a critical component in the [upstash/context7](https://github.com/upstash/context7) repository, designed to help AI agents identify the correct library ID before querying documentation. Rather than implementing local ranking logic, the tool leverages the Context7 API's sophisticated relevance algorithms to match user intent with the most appropriate library identifier.

## Understanding the `resolve-library-id` Tool Workflow

The tool operates as a thin wrapper that forwards structured requests to the Context7 SDK. It accepts natural language inputs and transforms them into ranked library identifiers through a series of coordinated API calls.

### Input Parameters

When invoked, `resolve-library-id` receives two critical inputs that drive the selection process:

- **`query`** – The user's original question or task description. This parameter is essential because the Context7 API uses it to determine relevance ranking.
- **`libraryName`** – The textual identifier or partial name of the target library (e.g., `"react-query"` or `"next.js"`).

These parameters are defined in [`packages/tools-ai-sdk/src/tools/resolve-library-id.ts`](https://github.com/upstash/context7/blob/main/packages/tools-ai-sdk/src/tools/resolve-library-id.ts), where the tool constructs a `Context7` client instance using the provided API key.

### Delegating to the Context7 API

Rather than performing string matching locally, the tool instantiates a `Context7` client and invokes the `searchLibrary` method:

```typescript
// From packages/tools-ai-sdk/src/tools/resolve-library-id.ts
const client = new Context7({ apiKey });
const results = await client.searchLibrary(query, libraryName, { type: "txt" });

```

This call triggers the SDK's `SearchLibraryCommand` (located in [`packages/sdk/src/commands/search-library/index.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/commands/search-library/index.ts)), which encodes the parameters into GET requests targeting the `/v2/libs/search` endpoint.

## How the Context7 API Ranks Library Matches

The actual selection logic resides entirely within the Context7 backend infrastructure. When the SDK sends the request to `/v2/libs/search`, the API performs sophisticated relevance scoring to determine which library best matches the user's intent.

### Relevance Algorithm

The Context7 API evaluates the textual `query` against all libraries matching the provided `libraryName`. The ranking algorithm considers:

- **Semantic relevance** – How closely the library's documentation content aligns with the user's specific question.
- **Library specificity** – Preference for official or canonical implementations over forks or unofficial mirrors.
- **Version currency** – Prioritization of stable, recent releases when multiple versions exist.

The API returns an ordered array where the most relevant library occupies the first position.

### Response Formatting

Once ranked, the results flow back through the SDK's formatting layer. The `SearchLibraryCommand` utilizes `formatLibrariesAsText` (defined in [`packages/sdk/src/utils/format.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/utils/format.ts)) to convert the `Library` objects into a human-readable plain-text list:

```typescript
// From packages/sdk/src/commands/search-library/index.ts
const formatted = formatLibrariesAsText(libraries);

```

This formatting preserves the API's ranking order, ensuring that the first entry in the text output represents the best match.

## Implementation Details in the Context7 SDK

The library resolution pipeline spans multiple packages within the monorepo, each handling specific responsibilities:

| File | Purpose |
|------|---------|
| [`packages/tools-ai-sdk/src/tools/resolve-library-id.ts`](https://github.com/upstash/context7/blob/main/packages/tools-ai-sdk/src/tools/resolve-library-id.ts) | Defines the tool interface and orchestrates the `Context7` client initialization. |
| [`packages/sdk/src/client.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/client.ts) | Exposes the `searchLibrary` method that constructs `SearchLibraryCommand` instances. |
| [`packages/sdk/src/commands/search-library/index.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/commands/search-library/index.ts) | Implements HTTP communication with `/v2/libs/search` and handles response formatting. |
| [`packages/sdk/src/utils/format.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/utils/format.ts) | Contains `formatLibrariesAsText` for converting library arrays to ranked text output. |

This architecture ensures that the `resolve-library-id` tool remains lightweight while leveraging the full capabilities of the Context7 search infrastructure.

## Practical Example: Using `resolve-library-id` in an AI Agent

The following example demonstrates how an AI agent uses `resolve-library-id` to dynamically resolve library identifiers before fetching documentation:

```typescript
import { resolveLibraryId, queryDocs } from "@upstash/context7-tools-ai-sdk";
import { generateText, stepCountIs } from "ai";
import { openai } from "@ai-sdk/openai";

const { text } = await generateText({
  model: openai("gpt-4o"),
  prompt: "Show me how to paginate in React Query",
  tools: {
    // Step 1: Resolve the library ID using the user's query context
    resolveLibraryId: resolveLibraryId(),
    // Step 2: Fetch documentation using the resolved ID
    queryDocs: queryDocs(),
  },
  stopWhen: stepCountIs(5),
});

/* Typical execution flow:
   1. resolveLibraryId receives:
      { query: "Show me how to paginate in React Query", 
        libraryName: "react-query" }
   
   2. Returns ranked results:
      "/tanstack/react-query"   (best match - official TanStack package)
      "/react-query/react-query" (community fork or older version)
   
   3. Agent extracts first entry ("/tanstack/react-query") and 
      passes it to queryDocs for documentation retrieval.
*/

```

In this workflow, the `resolve-library-id` tool ensures the agent retrieves documentation from the most authoritative source by leveraging the Context7 API's relevance ranking.

## Summary

- The `resolve-library-id` tool delegates all ranking decisions to the Context7 API rather than implementing local matching logic.
- It sends the user's original `query` and target `libraryName` to the `/v2/libs/search` endpoint via the SDK's `searchLibrary` method.
- The Context7 backend ranks libraries by semantic relevance to the user's question, returning the best match first in the response.
- Results flow through [`packages/sdk/src/commands/search-library/index.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/commands/search-library/index.ts) and [`packages/sdk/src/utils/format.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/utils/format.ts) before returning as formatted text to the caller.

## Frequently Asked Questions

### How does the `resolve-library-id` tool handle ambiguous library names?

When multiple libraries share similar names (such as forks or unofficial ports), the tool forwards all candidates to the Context7 API. The API's ranking algorithm evaluates the user's specific `query` against each candidate's documentation content, typically prioritizing official or canonical implementations. The tool then returns the full ranked list, allowing the caller to select the first entry or review alternatives.

### What parameters does the `resolve-library-id` tool require?

The tool requires two primary parameters: `query` (the user's natural language question or task description) and `libraryName` (the textual identifier of the target library). Additionally, the tool initialization requires a Context7 API key to authenticate requests to the backend service. These parameters are processed in [`packages/tools-ai-sdk/src/tools/resolve-library-id.ts`](https://github.com/upstash/context7/blob/main/packages/tools-ai-sdk/src/tools/resolve-library-id.ts).

### Can I customize the ranking algorithm used by `resolve-library-id`?

No, the ranking algorithm is not customizable through the tool interface. The relevance scoring is performed server-side by the Context7 API at the `/v2/libs/search` endpoint. The tool acts as a transparent proxy that returns the API's ranked results. If you require different ranking behavior, you would need to implement post-processing logic on the client side after receiving the ordered list from the tool.

### How does the tool format the library search results?

The tool returns results as plain text through the SDK's `formatLibrariesAsText` utility located in [`packages/sdk/src/utils/format.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/utils/format.ts). This formatter converts the array of `Library` objects returned by the API into a human-readable list while preserving the API's relevance ranking. The `SearchLibraryCommand` in [`packages/sdk/src/commands/search-library/index.ts`](https://github.com/upstash/context7/blob/main/packages/sdk/src/commands/search-library/index.ts) orchestrates this formatting before returning the final output to the tool caller.