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get_inlay_hints

Retrieve inline code annotations like inferred types and parameter labels from language servers to understand compiler knowledge without explicit type declarations.

Instructions

Get inlay hints for a range within a document via LSP (textDocument/inlayHint). Inlay hints are inline annotations that IDEs display in source code — typically inferred type names (e.g. : string) and parameter name labels (e.g. count:). Useful in languages with type inference (TypeScript, Rust, Go) to see what the compiler knows without reading every type annotation. Returns an array of InlayHint objects, each with a position, label, and optional kind (1=Type, 2=Parameter). Returns an empty array if the language server does not support inlay hints.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
language_idNo
start_lineYes
start_columnYes
end_lineYes
end_columnYes
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses key behavioral traits: it's a read operation (implied by 'Get'), returns an array of InlayHint objects with specific structure, and returns empty array if unsupported. However, it doesn't mention error conditions, performance characteristics, or authentication needs that might be relevant for an LSP tool.

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 efficiently structured with three focused sentences: purpose definition, usage context, and return behavior. Every sentence adds value without redundancy. It's appropriately sized for the tool's complexity and front-loads the core functionality.

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

Completeness3/5

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

Given the tool's moderate complexity (6 parameters, LSP integration), no annotations, and no output schema, the description provides good purpose and usage context but leaves significant gaps. The complete lack of parameter documentation and limited behavioral disclosure makes this incomplete for confident tool selection and invocation.

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

Parameters2/5

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

With 0% schema description coverage and 6 parameters, the description provides no information about any parameters. It mentions 'a range within a document' which hints at line/column parameters but doesn't explain file_path, language_id, or the specific coordinate system. The description fails to compensate for the complete lack of schema documentation.

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 with specific verb ('Get') and resource ('inlay hints for a range within a document via LSP'), explaining what inlay hints are with concrete examples. It distinguishes this tool from siblings like get_completions or get_diagnostics by focusing specifically on inline type/parameter annotations rather than other code intelligence features.

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 provides clear context about when this tool is useful ('Useful in languages with type inference like TypeScript, Rust, Go'), giving practical guidance. However, it doesn't explicitly state when NOT to use it or name specific alternative tools for related functionality, which prevents a perfect score.

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

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