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Random Tables

by io.github.pipeworx-io
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Get Random Table

get_random_table
Read-onlyIdempotent

Pipeworx original random tables: fetch one built-in table in full — its title, genre, description, and every raw entry (text + weight) — without rolling. Entry text may contain unresolved {{table:}} references; roll_table resolves those at roll time.

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": {
      "table": "loot"
    },
    "name": "get_random_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableYesBuilt-in table id, e.g. "loot", "npc_full", "encounters_fantasy". Call list_random_tables to see every id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower. The description adds a non-obvious behavioral fact beyond the annotations: entry text may contain unresolved {{table:<id>}} references that only roll_table resolves, which directly affects how an agent should interpret the returned data.

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?

Two dense sentences, front-loaded with what is returned before the caveat about unresolved references. Every clause carries information an agent needs; nothing is 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?

With no output schema, the description carries the burden of describing the return value and does so concretely (title, genre, description, raw entries with text + weight), plus the reference caveat. Nothing essential for correct invocation 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% and the single 'table' parameter is documented with examples and a pointer to list_random_tables. The description only restates that one table is fetched, adding no syntax or format detail beyond the schema, so the baseline 3 applies.

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 ('fetch one built-in table in full') plus the exact scope of the payload (title, genre, description, every raw entry with text + weight). It also contrasts itself with the sibling roll_table ('without rolling'), so an agent can distinguish the two 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 Guidelines4/5

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

The 'without rolling' clause gives clear context for when this is the right tool versus roll_table, and the schema points to list_random_tables for discovering ids. It does not state explicit exclusions or a full when-not-to-use rule, but the selection condition is unambiguous.

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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