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nagendra-kon

repodigest-mcp

by nagendra-kon

get_symbol_signature

Read-only

Retrieve a Python function, class, or method signature and docstring without reading the full file. Specify a symbol name and optional path to get token-efficient code context.

Instructions

Return a Python symbol's signature and docstring without its body.

Far cheaper than reading the file. Works for functions, classes (methods listed as signatures) and methods.

Args: symbol_name: Qualified name (pkg.mod.Class.method) or any dotted suffix of it (Class.method, method). Ambiguous suffixes return the candidates. path: Repository root to search (default: the server's working directory).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo.
symbol_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

The description adds meaningful behavioral detail beyond the readOnlyHint: it excludes the function body, handles classes by listing methods as signatures, and returns candidates for ambiguous suffixes. These are concrete, non-obvious behaviors that help an agent predict results without contradicting the annotations.

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 compact and front-loaded with the core purpose, followed by a cost/benefit note and efficient parameter semantics. Every sentence adds value and there is no redundant or filler content.

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 output schema exists, the description does not need to explain return values. It covers purpose, behavior, ambiguity handling, and both parameters, leaving no obvious gap for an agent to invoke the tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden. It thoroughly explains symbol_name, including qualified names, dotted suffixes, and ambiguity resolution, and documents path's default as the server working directory. This fully compensates for the schema's lack of descriptions.

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 opens with the specific action and resource: "Return a Python symbol's signature and docstring without its body." It clearly defines what the tool does and distinguishes it from siblings like get_symbol_dependencies by focusing on signatures rather than dependencies and by explicitly excluding the body.

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?

"Far cheaper than reading the file" gives a clear when-to-use context for retrieving signature-only information. However, it does not explicitly contrast with sibling tools or state when not to use it, so it stops short of full usage routing.

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