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tascan_register_agent

Idempotent

Register a new AI agent in the agent registry. The agent will appear in tascan_list_agents and can receive dispatched tasks. Self-registration for AI agents joining the TaScan network. REQUIRES the agent:dispatch permission (defining a dispatch target is a dispatch permission); inbox_id must be a task list (event) in your organization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUnique agent ID (e.g. "my-agent-1")
nameYesDisplay name (e.g. "Research Bot")
typeYesAgent type
modelNoModel powering this agent (e.g. "claude-sonnet-4-6")
inbox_idYesTask list ID this agent monitors for new tasks
locationNoWhere the agent runs (e.g. "AWS us-east-1")
worker_idNoTaScan worker ID for this agent
descriptionNoWhat this agent does
capabilitiesYesTask type prefixes this agent handles (e.g. ["RESEARCH", "WRITE"])

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover readOnly=false, destructive=false, and idempotent=true. The description adds meaningful behavioral context beyond those: the agent becomes visible in listingscars and can receive dispatched tasks, and permission/inbox constraints must hold. This gives the agent a clear model of side effects and prerequisites.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficient, front-loads the core purpose, and each sentence adds context. The parenthetical '(defining a dispatch target is a dispatch permission)' is somewhat redundant and slightly confusing, keeping it from a perfect 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter mutation tool with no output schema, the description covers purpose, requirements, and effects but omits return value or success confirmation details. It does mention the visible outcome (appears in list_agents), yet leaves the agent to infer what the response looks like.

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 the baseline is 3. The description adds useful semantic detail for inbox_id (must be a task list/event in your organization), but it doesn't meaningfully elaborate on the other 8 parameters. This exceeds the baseline slightly but not enough to warrant a 4.

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 states a specific verb and resource: 'Register a new AI agent in the agent registry.' It clearly distinguishes this tool from siblings like create_worker or register_asset by focusing on AI agent registration in the agent registry MkDocs, and it even names the direct effect (appears in tascan_list_agents, can receive dispatched tasks).

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 gives clear context: 'Self-registration for AI agents joining the TaScan network.' It also states hard prerequisites (agent:dispatch permission, inbox_id must be an event task list). It doesn't explicitly exclude alternatives or name competing tools, so it stops short of a full 5.

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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