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okenjioxx

Roblox Executor MCP Server

by okenjioxx

Suggest tools for a keyword, ranked by past success

suggest-tools
Read-only

Finds relevant Roblox executor tools from a natural-language goal using intent aliases, field-aware ranking, and a session success bias to surface better matches.

Instructions

Surface the right tool faster from a natural-language goal. Uses intent aliases and field-aware ranking, then adds a small past-success bias so tools that have worked in this server session float above equally relevant untouched tools. Returns exact signatures, required inputs, definition quality, phase/cost, capabilities, outputs, mutation/client flags, match reasons, and usage stats. Pass { keyword } (required), { limit } (default 10), and optional { category }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum tools to return, default 10.
keywordYesNatural-language goal or keyword, e.g. 'find the player's money' or 'click a UI button'.
categoryNoOptional: restrict to one category.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0-spies.2

TDQS

A3.7/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true; the description adds real behavioral context beyond that, disclosing the intent-alias/field-aware ranking and the session-local past-success bias that reorders equally relevant results. It also enumerates the returned fields, which is valuable given no output schema exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the purpose before the ranking mechanics and the return-field list. The long enumeration of return fields is dense but earns its place given the absence of an output schema.

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?

For a read-only discovery tool with no output schema, the description covers purpose, ranking behavior, and the shape of the response, which is what an agent needs to call it correctly. Only the relationship to the closest sibling (list-tools) is left implicit.

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%, so the schema already documents keyword, limit (default 10), and category. The description restates the same three parameters with defaults and required/optional status, adding no syntax or semantic detail beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('surface the right tool') scoped to a natural-language goal, and the title adds the keyword/ranking angle. It is clearly distinct from a plain listing tool like list-tools, though it never names that sibling explicitly.

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

Usage Guidelines3/5

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

'Surface the right tool faster from a natural-language goal' implies the use case (goal-based discovery rather than enumeration), but there is no explicit when-not guidance and no alternative sibling is named for comparison against list-tools or tool-schema.

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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