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delegate_parallel

Run independent tasks as parallel sub-agents and get all reports in one answer. Ideal for non-dependent work; failed tasks are flagged without affecting other results.

Instructions

Run several independent sub-agents at once and return every report in one answer.

This is the tool to use whenever the work splits into pieces that do not depend on each other: "summarise each of these four modules", "check these three services for the same misconfiguration", "for each failing test, find the cause". Running them concurrently on one NIM connection is much faster than calling delegate in a loop, and all the reading still happens outside your context.

Every string in tasks is a separate cold-start sub-agent with no memory of the others and no view of this conversation. Do not chain them - task 2 cannot use task 1's answer. If the work is genuinely sequential, use delegate one step at a time. Each task string must be self-contained and say what output you want, exactly as for delegate.

Parameters: tasks - list of self-contained task strings, one sub-agent each. profile - "general" (default), "researcher", "coder", or "reviewer"; applies to all. files - paths handed to every sub-agent up front. model - override the NIM model (default stepfun-ai/step-3.7-flash).

Concurrency is capped at SUBMCP_MAX_PARALLEL (default 4); extra tasks queue. All sub-agents are read-only here - there is no write parameter, because concurrent edits to one working tree are how you lose work. Use delegate with write=True for edits.

Returns one markdown document with a ## Task N section per input task, in the order you supplied them. A task that fails gets its own section marked FAILED with the reason; the other reports still come back intact, so one bad task never costs you the rest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNo
modelNo
tasksYes
profileNogeneral

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations are present, so the description carries the full burden. It discloses that each task is a cold-start sub-agent with no memory, that concurrency is capped at SUBMCP_MAX_PARALLEL, that sub-agents are read-only with no `write` parameter, and that failures are isolated into a FAILED section without losing other results.

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 structured with a clear first line, usage conditions, parameter breakdown, and return behavior. Despite being detailed, every sentence adds critical information without redundancy.

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?

Given the complexity of parallel sub-agents, the description covers use cases, restrictions, parameters, return format, failure handling, and the relationship to the sibling `delegate` tool. No crucial behavioral aspect is left unexplained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema has 0% description coverage, the description includes a parameter list that explains each argument: self-contained tasks, profile options, files given to every sub-agent, and model override. This compensates fully for the missing schema descriptions.

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?

Clearly states it runs several independent sub-agents concurrently and returns all reports in one answer. Explicitly distinguishes from the sibling `delegate` by noting it is for splitting work into independent pieces, making it unambiguous.

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?

Provides explicit when-to-use with examples, explicitly discourages chaining tasks, and directs users to `delegate` for sequential work and for edits (with write=True). Also specifies that each task must be self-contained.

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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