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Heliyos MCP server

Heliyos MCP server

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by heliyos-ai

List workers

heliyos_workers_list
Read-onlyIdempotent

Lists a workspace's AI agent workers, including built-in and custom agents, with IDs, types, active status, descriptions, and optional trigger details; supports filtering by type or active state.

Instructions

Lists the workspace's workers (AI agents): the built-in default ones and custom ones, each with its id, type, active flag, description and triggers. Returns every worker in one page (a workspace has a handful). Use heliyos_workers_get for a worker's instructions, heliyos_runs_list with worker_id for its runs. Returns structuredContent {workers:[{id, name, type, is_active, ...}]}.

Input Schema

NameRequiredDescriptionDefault
typeNoOnly built-in (default) or only custom workers.
is_activeNoOnly active (true) or only inactive (false) workers.
response_formatNo"concise" (default) returns one row per worker; "detailed" returns each worker's triggers too.concise

Output Schema

NameRequiredDescriptionDefault
workersYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuine behavioral context beyond that: no pagination ("Returns every worker in one page (a workspace has a handful)") and the structuredContent envelope. It does not mention ordering, which is the only real gap.

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?

Three tight sentences: what it returns, the no-pagination constraint, then sibling routing. Front-loaded and every sentence carries information an agent needs.

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?

For a zero-required-parameter list tool with an output schema, annotations and full schema coverage, nothing material is missing. Scope, result cardinality, return shape and alternatives are all addressed.

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% with two enums fully documented, so the schema does the heavy lifting. The description only lightly echoes the type filter ("built-in default ones and custom ones") and the triggers field tied to response_format=detailed; it adds little beyond the schema's own text.

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?

States a specific verb and resource ("Lists the workspace's workers (AI agents)") plus the scope of what is returned (default and custom, with id, type, active flag, description, triggers). This clearly separates it from heliyos_workers_get, which fetches a single worker's instructions.

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?

Explicitly routes the agent to alternatives with conditions: heliyos_workers_get for a worker's instructions and heliyos_runs_list with worker_id for its runs. It also preempts a common question by saying results come in one page, so no pagination handling is needed.

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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