Skip to main content
Glama

suggest_imports

Find fully qualified import candidates for unresolved Java types by searching project sources, JDK, and libraries, sorted by relevance.

Instructions

Find import candidates for unresolved type.

USAGE: suggest_imports(typeName="List") OUTPUT: List of matching types with fully qualified names and relevance

Searches project sources, JDK, and libraries for types matching the simple name. Results are sorted by relevance (java.util types ranked higher than java.awt, etc.).

Requires load_project to be called first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNameYesSimple type name to find imports for (e.g., 'List', 'Map')
maxResultsNoMaximum candidates to return (default 20)
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears full responsibility. It discloses that the tool searches project sources, JDK, and libraries, and sorts results by relevance. It also notes the load_project prerequisite. However, it does not mention whether the tool is read-only, idempotent, or what happens if the type is already resolved.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (4 sentences) and well-structured, front-loading the purpose and example. Every sentence adds value: purpose, usage, output, search sources, sorting, prerequisite. No unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema, the description sufficiently describes the output (list of types with names and relevance) and sorting behavior. It also correctly specifies the prerequisite (load_project). The context is complete for an agent to understand and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters. The description adds a usage example (e.g., typeName='List') but does not elaborate on parameter semantics beyond what the schema already provides. The baseline of 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Find import candidates for unresolved type.' It provides a usage example, specifies the output (list of matching types with fully qualified names and relevance), and distinguishes itself from sibling tools like organize_imports (which actually performs imports) and search_symbols (broader search).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states a prerequisite: 'Requires load_project to be called first.' It also provides a usage example and explains the output format. However, it does not explicitly state when to use this tool versus alternatives or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pzalutski-pixel/javalens-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server