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TaScan

by io.github.snowbikemike

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.

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"])

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover idempotency and non-destructive behavior. The description adds useful behavioral context: the registered agent will appear in tascan_list_agents and can receive dispatched tasks. It does not disclose edge cases like duplicate ID handling or auth requirements, but supplements the annotations well.

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 concise sentences that front-load the primary action and immediately provide key behavioral outcomes. Every word earns its place, with no unnecessary 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?

The description covers the main purpose and post-registration effects, and the schema fully documents all parameters. It omits error/edge cases such as duplicate IDs or permissions, but given the tool's moderate complexity and good annotations, it is sufficiently complete for effective use.

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%, meaning all 9 parameters are fully documented in the input schema. The description adds no additional parameter-level meaning, so a baseline score 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 clearly states the tool's action: registering a new AI agent in the agent registry. It further distinguishes itself by noting the agent will appear in tascan_list_agents and can receive dispatched tasks, which is specific and unique among siblings.

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 provides clear context: 'Self-registration for AI agents joining the TaScan network' implies when this tool should be used. However, it does not explicitly exclude alternatives like tascan_create_worker or mention scenarios where this tool should not be used, so it stops short of a 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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TDQS

A3.5/5.0
Disambiguation4/5

Most tools map to a distinct resource+action pair, and the descriptions clearly separate entities like tasks, subtasks, workers, invoices, zones, assets, and reports. A few close pairs (get_report vs generate_report, dispatch_instruction vs dispatch_to_agent, analyze_issue vs auto_resolve) require careful reading, but the descriptions are detailed enough to disambiguate them.

Naming Consistency4/5

The vast majority follow a tascan_verb_noun pattern with consistent create/get/list/update/delete verbs. Minor deviations like condition_history, server_info, zone_compliance, and one-word find slightly break the otherwise predictable pattern.

Tool Count1/5

At 69 tools, this is far beyond what an agent can efficiently consider, and it bundles several distinct domains into one MCP surface. Even if each tool is individually useful, the combined set is an extreme mismatch for a coherent tool interface.

Completeness4/5

The surface covers nearly the full lifecycle for projects, events, tasks, subtasks, workers, reports, invoices, zones, assets, issues, and communications. Minor gaps exist (no explicit asset updates/decommissioning, no cancel_invite, no delete_zone), but the main workflows have no dead ends.

Resources