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agent-lsp

agent-lsp

by blackwell-systems
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Hybrid

get_document_symbols

Get a file's structural overview by retrieving all defined symbols as a hierarchical tree or compact markdown outline for efficient analysis.

Instructions

Get all symbols defined in a document via LSP (functions, classes, variables, methods, etc.). Returns a hierarchical DocumentSymbol tree or flat SymbolInformation list depending on server support. Use this to get a structural overview of a file. Pass format: "outline" for compact markdown output (name [Kind] :line) optimized for LLM consumption — ~5x fewer tokens than JSON for the same structural information.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file_path": "<file_path>"
    },
    "name": "get_document_symbols"
  }
}

Input Schema

NameRequiredDescriptionDefault
formatNo
file_pathYes
language_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.16.0
  2. Removedv0.15.0
  3. Addedv0.11.1
  4. Removedv0.10.0
  5. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that return format depends on server support (hierarchical vs flat) and that outline format reduces tokens. Missing details: whether the tool is read-only, triggers LSP communication, or has side effects.

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 two sentences, efficiently covering purpose, return format, usage guidance, and optional format behavior. No filler or redundancy. Information is front-loaded.

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

Completeness4/5

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

Given no output schema and 3 parameters, the description covers the core functionality well. It explains the return format variability and optimizes for LLM usage. Missing: description of language_id, expected side effects, or relationship to sibling tools beyond implicit differentiation.

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 0%, so the description must compensate. It explains the 'format' parameter with a concrete value ('outline') and its benefit, and implies file_path as the document. However, language_id is not mentioned at all, leaving its purpose unclear.

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 gets all symbols defined in a document via LSP, listing specific symbol types. It implicitly distinguishes from workspace-level siblings like get_workspace_symbols by focusing on a single file. The mention of hierarchical vs flat output adds precision.

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 usage guidance: 'Use this to get a structural overview of a file.' It also promotes the outline format for LLM consumption. However, it does not explicitly exclude use cases like workspace-wide searches or navigation, which are covered by sibling tools.

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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