Skip to main content
Glama

algernon_orchestrate

Decompose a goal into parallel sub-tasks, dispatch them across a fleet of LLM workers, and retrieve the plan and results to keep your main context lean.

Instructions

One shot: plan THEN dispatch. Hand it a goal; it splits the goal into k tight sub-tasks and fans them out across the fleet, then returns the plan and all results. Orchestrate a fleet, spend fewer tokens — and stay free to think.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNohow many parallel sub-tasks to split into
goalYeswhat you want accomplished
modelNooptional worker model override
max_parallelNohow many workers run at once

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burdenstant it uses 'plan THEN dispatch', describes the splitting and fan-out behavior, and mentions it returns the plan and all results. It does not disclose side effects, error behavior, or resource implications beyond token savings, but the core execution pattern is transparent.

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?

The description is two sentences, efficiently front-loaded with the core 'One shot: plan THEN dispatch' hook, then covers the execution flow, returned payload, and benefit. Every sentence is informative with very little marketing fluff.

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 complex orchestration tool with four parameters, no output schema, and no annotations, the description gives the essential interaction flow, including what it accepts, what it executes, and what it returns. It lacks output-structure details or caveats about executing real work, but the high-level contract is sufficient for selection and invocation.

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?

The input schema already documents all four parameters with descriptions, giving 100% coverage. The description adds only a minimal semantic link ('k tight sub-tasks' echoes the k parameter) and does not enrich meaning beyond the schema, so the baseline of 3 is appropriate.

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 uses a specific verb-plus-resource structure ('one shot: plan THEN dispatch'), explains it splits a goal into k sub-tasks and fans them out across the fleet, and clarifies it returns both plan and results. This clearly differentiates it from siblings like algernon_plan or algernon_dispatch by showing it combines both in a single call.

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 description clearly implies when to use this tool: when you want a complete orchestration workflow in one call by handing it a goal. It states the benefit of spending fewer tokens)Skip but does not explicitly name alternatives or give exclusion conditions, so it stops short of full when-not guidance.

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