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mark-burg

reference-mcp

by mark-burg

get_file_outline

Retrieve a nested outline of a Python file or directory—showing classes, methods, functions, and module variables with line numbers—without reading the full file body.

Instructions

List the symbol skeleton of a file or directory WITHOUT reading bodies — the cheapest way to understand what a file contains.

Returns a nested outline (classes, methods, functions, module vars) with line numbers. Prefer this over reading a whole file when you only need its shape.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesRepo-relative path to a .py file, or a directory (e.g. 'pkg/' ).
response_formatNo'concise' (names) or 'detailed' (signatures + docstrings).concise

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the operation is cheap (cost hint), does not read bodies, and returns a nested outline with line numbers. Could add limits (e.g., only for Python files based on path schema) but is fairly transparent.

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?

Two concise sentences front-load the purpose, with no fluff. The second sentence adds important detail about return content. Every phrase earns its place.

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?

The description covers what, why, and when to use the tool. Given the simple read-only nature with 2 well-documented parameters and an output schema, it is largely complete. Could mention that it works only for Python files (based on path schema) but otherwise sufficient.

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 clear parameter descriptions. The description does not add extra semantics beyond what the schema provides, but it reinforces the return context ('outline with line numbers'). Baseline score of 3 is appropriate.

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?

Clearly states the action ('List the symbol skeleton') and resource ('a file or directory'), with the key benefit of NOT reading bodies. Distinguishes itself from reading a whole file, which is a sibling operation.

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?

Explicitly advises to prefer this over reading a whole file when only the shape is needed. Implicitly contrasts with tools like search_code or find_references, but does not enumerate when to avoid it.

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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