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Run an orchestrator/worker collaboration

run_orchestrator

Coordinates a task among available specialists, classifies its complexity, assigns focused missions, then synthesizes outputs into a run report with success and evidence status.

Instructions

A Chief provider classifies the task's complexity, picks the minimum sufficient set of specialists, gives each one coherent mission, then a synthesizer merges their results into one final answer. Specialist count is capped by complexity (simple 1, normal 3, deep 4). Returns a run report: SUCCESS/DEGRADED/FAILED plus an evidence label, and a deep answer with no evidence behind it is marked UNVERIFIED in the output itself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesThe overall task to accomplish.
budgetNoConstraints the Chief must plan within. maxSpecialists is enforced; cost and latency are stated to the Chief as planning constraints.
workersYesThe specialists available to the Chief: registered agent ids, or full inline definitions.
synthesizerNoProvider that synthesizes specialist results. Defaults to the orchestrator.
orchestratorYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden. It openly describes the orchestration flow, the complexity-based specialist cap, and the run report statuses including the evidence label and UNVERIFIED marking. It does not mention potential costs, external calls, or side effects, but the main behavioral contract is clearly disclosed.

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 three dense sentences, each earning its place: the first explains the workflow, the second gives the specialist cap rule, and the third summarizes output behavior. Information is front-loaded and free of filler.

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 multi-agent tool with no output schema, the description covers the execution model, operational constraints, and key output semantics. Minor gaps remain, such as the exact run report structure and provider/model selection details, but those are partially covered by the input schema.

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 coverage is high at 80%, so the baseline is 3. The description adds useful orchestration context, such as workers being candidate specialists, synthesizer defaulting to the orchestrator, and the relevance of evidence labels, but it does not map individual parameters in detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs an orchestrator/worker collaboration: a Chief classifies complexity, selects specialists, and a synthesizer merges results. It is specific about the execution model, though it does not explicitly differentiate from sibling tools like run_pipeline or run_debate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

The description implies when to use this tool: for complex tasks requiring delegation to multiple specialists and synthesis into a final answer. It does not explicitly state when not to use it or name alternatives, leaving usage guidance implicit rather than explicit.

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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