Skip to main content
Glama

batch

Destructive

Run multiple game actions in one ordered call, stopping at the first refusal by default or continuing through all rows when configured. Returns per-row results and optional stop point.

Instructions

Many orders in one call, in order: actions is a list of {tool, args} rows -- the rows every read hands back, old or new names alike -- each answered under results; the first refusal stops the rest (stop_on_refusal=false runs them all). Not inside: the turn's wait / finish / end, a load, the seat, the exit, a batch. turn(action='finish', actions=[...]) runs a batch and ends the turn in one call. Returns {ok, results: [one reply per row], stopped_at?}; the rows act on the game as the orders they carry.

Input Schema

NameRequiredDescriptionDefault
forceNotake over this turn's claim held by another client of my seat
actionsYesthe rows to run in order, [{tool, args}], as every read hands them back
stop_on_refusalNostop at the first refused row (default true); false runs them all

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark the tool as destructive, non-idempotent, and not read-only. The description adds useful behavioral detail beyond that: the first refusal stops subsequent rows by default, stop_on_refusal=false runs them all, and it specifies the return shape including results and stopped_at.

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?

The description is front-loaded with the core purpose ('Many orders in one call, in order') and uses a single dense paragraph. The exclusion list and alternative mention are useful but make the sentence somewhat cluttered.

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 batch executor with no output schema, the description supplies the return structure and failure semantics, plus important exclusions and an alternative path via turn(action='finish'). The only minor gap is that the force parameter is not described here, though the schema covers it.

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 schema already documents actions, stop_on_refusal, and force. The description reinforces the row format and refusal behavior but does not add syntax or meaning beyond what the schema provides, and it does not mention the force parameter.

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?

The description states a specific operation: runs many orders (a list of {tool, args} rows) in one call, in order. It also distinguishes this from turn(action='finish', actions=[...]) and explicitly excludes certain operations, so an agent can identify the tool's role without opening the 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?

It explicitly says what is not allowed inside a batch (wait/finish/end, load, seat, exit, another batch) and names the alternative for combining a batch with ending the turn. This gives clear when-to-use and when-not-to-use guidance.

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