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Glama

Preset swarm (jury / research / red team / council)

preset_swarm

Run a named preset panel of agents from different model families in parallel on the same material, replacing hand-built tasks so repeated runs stay comparable.

Instructions

Run a PREDEFINED swarm: a named panel of agents from different model families, each in its own role, all working on the same material in parallel. One call instead of building agent_swarm tasks by hand, and the same panel every time, so two runs (two applications, two drafts) can be compared.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
watchNoIf true, open the live "Agent Swarm" dashboard, one card per member, captioned with its role.
presetYesThe preset's name, e.g. "jury", "research", "red-team", "council", or one of the user's own.
materialYesThe text the panel works on, in full.
timeout_sNoPer-member timeout in seconds (default: the preset's own, 240-360s for the built-ins). opencode members get at least 300s.
workspaceNoDirectory the members run in, and whose .agent-intern/swarms/ presets are included (default: server cwd).
max_concurrencyNoMembers running at once (default 4).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.32.1

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=false. The description adds useful behavior beyond that: members run in parallel on the same material, and the panel composition is deterministic across runs. It says nothing about cost, failure/timing behavior, or side effects of an open-world multi-agent run, so it only partially carries the burden for a non-read-only, non-idempotent tool.

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 tight sentences, front-loaded with the action and scope, then the differentiation and the reproducibility benefit. No filler, no restatement of the title.

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?

An output schema exists, so return values need no explanation, and the schema covers all parameters including defaults. The description adequately conveys what the tool does and why it exists; the only gap is the implicit dependency on a valid preset name, which the description never connects to the swarm_presets sibling.

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 all six parameters (including preset, material, timeout_s, workspace, max_concurrency, watch) are already documented in the schema. The description adds no parameter-level detail such as preset-name syntax or material-size expectations, 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?

Specific verb+resource: 'Run a PREDEFINED swarm' followed by a concrete definition (named panel of agents from different model families, each in its own role, parallel work on the same material). It explicitly contrasts with the sibling agent_swarm ('instead of building agent_swarm tasks by hand'), so the agent can distinguish them 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?

Clear context: use it when you want a canned panel rather than hand-built agent_swarm tasks, and it notes the reproducibility benefit ('same panel every time') that makes two runs comparable. It does not mention prerequisites such as needing an existing preset name (the swarm_presets sibling is never referenced) or any when-not condition.

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