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List Random Tables

list_random_tables
Read-onlyIdempotent

Pipeworx original random tables: list every built-in table id, title, genre and entry count, optionally filtered to one genre ("fantasy", "scifi" or "modern"). Genre-agnostic tables (loot, weather, npc_*, complication, plot_hook, rumour, settlement_quirk, npc_full) are included under every genre filter, since they apply regardless of setting.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "genre": "fantasy"
    },
    "name": "list_random_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault
genreNoOptional genre filter. Omit to list every table.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent and non-destructive, so safety is covered. The description adds genuine behavioral value beyond them: the inclusion rule for genre-agnostic tables (loot, weather, npc_*, etc.) under every genre filter, plus the exact fields returned. No return format details beyond the field list are given, but that is a minor gap.

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?

Two sentences, front-loaded with the core action and output fields; the second sentence is dense but earns its place by clarifying filter semantics. Slightly list-heavy inside parentheses, but no filler.

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 naming exactly what is returned (id, title, genre, entry count). Combined with the filter semantics, an agent has everything needed to call and interpret this tool.

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

Parameters4/5

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

Schema coverage is 100% and the enum values are already documented, so the baseline is a 3. The description goes further by explaining the semantic consequence of the filter — which table families still appear — which is meaning the schema alone does not convey.

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 and resource ('list every built-in table id, title, genre and entry count') and enumerates the returned fields, which is unusually precise. The listing scope is inherently distinct from the roll-oriented siblings (roll_table, get_random_table, roll_custom_table), so an agent can route correctly without opening a schema.

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?

Clearly explains the conditional behavior of the optional genre filter, including the non-obvious rule that genre-agnostic tables appear under every filter. It does not explicitly name an alternative tool or state when to prefer listing over rolling, leaving that one step 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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