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roblox-logics-mcp

Find logics using a Luau API

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Find Roblox logic examples that use a specific Luau symbol or Roblox API, returning matching code snippets with surrounding lines. Use for exact code references, not conceptual prose search.

Instructions

Find logics whose example code uses a specific Luau symbol or Roblox API — 'UpdateAsync', 'BindToClose', 'ProcessReceipt', 'RaycastParams', 'task.defer'. Returns a short snippet with surrounding lines. This is a literal substring match over code blocks, not prose search: use search_logics for conceptual questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results.
symbolYesExact API name, method or identifier as it appears in code. Case-insensitive, no wildcards.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: it discloses the matching semantics (literal substring, not semantic/prose) and the return shape ('a short snippet with surrounding lines'). It stops short of a 5 because it says nothing about result ordering, truncation, or what happens when limit is exceeded.

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?

Three sentences, front-loaded with the core purpose, then the examples, then the disambiguation rule. Zero filler and every clause carries 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?

There is no output schema, and the description compensates by stating the return format ('short snippet with surrounding lines'). Combined with the 100%-documented parameter schema and the annotations, an agent has everything needed to invoke this 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 description coverage is 100% — 'symbol' is fully documented (exact API name, case-insensitive, no wildcards) and 'limit' carries max 20/default 5. The example symbols in the description loosely illustrate the accepted value format, but add little beyond the schema, so the baseline 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?

States a specific verb+resource ('Find logics whose example code uses a specific Luau symbol or Roblox API') and reinforces it with concrete example symbols like 'UpdateAsync' and 'task.defer'. It explicitly distinguishes itself from the sibling search_logics, so an agent can pick between them without opening either schema.

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

Usage Guidelines5/5

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

Gives an explicit routing rule: literal substring match over code blocks, 'use search_logics for conceptual questions.' It also names what this tool is NOT for ('not prose search'), which is exactly the when-not guidance an agent needs.

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