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okenjioxx

Roblox Executor MCP Server

by okenjioxx

List GC tables

list-gc-tables
Read-onlyIdempotent

Enumerate table objects from getgc(true), filtering with optional key/value queries to identify live Luau tables in a Roblox client.

Instructions

Enumerate table objects from getgc(true) with optional key/value query matching. Signature: { query: any?, limit: any?, threadContext: number? }. Phase: observe; cost=medium; idempotency=read-only. Requires: active-client. Capabilities: getgc. Produces: bounded-candidates. Safety: read-only. On failure: inspect tool-schema for exact fields, defaults, constraints, and an invocation example.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoOptional hard result/work budget used to keep output and runtime bounded.
queryNoOptional search text used to filter and rank bounded results.
threadContextNoOptional Roblox thread identity for this call; omit it to use the server default.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0-spies.2

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare read-only, idempotent, non-open-world, non-destructive, so the safety profile is covered. The description adds modestly useful context beyond that: cost=medium, capability getgc, and requires active-client. But 'Produces: bounded-candidates' is vague and no output/pagination behavior is described.

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

Conciseness3/5

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

The purpose is front-loaded, which is good, but the body is dense template boilerplate ('Signature', 'Phase', 'Capabilities', 'Produces', 'Safety') and the Signature block redundantly restates the schema. The 'On failure: inspect tool-schema' pointer is meta rather than useful content.

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, idempotent list tool with 100% schema coverage and full annotations, the description is largely sufficient: it names the source, the precondition, and the safety profile. It lacks any note on result volume/ordering, but nothing critical is missing.

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%, so the baseline is 3 and the schema already documents limit, query, and threadContext. The description adds little, and its phrase 'key/value query matching' slightly mischaracterizes the schema's 'search text' string parameter.

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 (enumerate) and resource (table objects from getgc(true)), plus the filtering behavior. It is distinguishable from list-gc-functions and find-tables-by-key, but it never explicitly names a sibling or contrast condition, so it falls short of a 5.

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?

Gives a precondition (Requires: active-client) and a phase marker (observe), which implies when the tool fits. However, it never states when NOT to use it or which alternative (find-tables-by-key, search-gc-value, filter-gc) to pick, leaving routing to inference.

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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