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register_agent

START HERE. One call: get $5 free credits + API key, instantly (no card, no human, no Stripe, ~5 seconds). Works immediately: query live DePIN telemetry (501 symbols, every value carries a verify_url you can check yourself), GPU inference, DAG manifold. Try get_data_dictionary first if you want the coverage spec, or GET https://kairossignal.com/try with zero setup. Nothing to cancel; credits just sit there until you spend them. Then list_products to see what $0.49+ buys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoOPTIONAL contact email (for delivery and topup notifications). Omit to register anonymously.
agent_nameYesYour agent name

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / required
      Previous value: -[
      -  "email",
      -  "agent_name"
      -]New value: +[
      +  "agent_name"
      +]
  2. Changed1 schema field changed
    • changedInput schema / properties / email / description
      Previous value: -"Contact email (for delivery and topup notifications)"New value: +"OPTIONAL contact email (for delivery and topup notifications). Omit to register anonymously."
  3. Added

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It discloses speed (~5 seconds), lack of payment/card/human involvement, and that credits persist. However, it does not describe side effects such as creating a persistent agent identity, potential uniqueness requirements on agent_name, or any account-related implications. It adds some useful context but omits important registration behavior.

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

Conciseness2/5

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

The description is overly promotional and includes irrelevant platform features (DePIN telemetry, GPU inference, DAG manifold) that do not help an agent call register_agent. It also mentions an external URL as an alternative onboarding path. The core instruction is padded with marketing, making it less concise than it should be.

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?

No output schema exists, so the description should state what the call returns; it does mention API key and $5 credits. It also gives a next step (list_products). However, it does not explain error conditions, whether agent_name must be unique, or how the returned API key should be used in subsequent calls. It is adequate but not complete for a registration tool.

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 100%, with brief descriptions for email and agent_name. The tool description does not add any meaning beyond the schema; it does not mention how agent_name is used or what happens if email is omitted. With full schema coverage, baseline 3 is appropriate.

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 conveys that calling this tool is the entry point to get an API key and $5 free credits, which implies agent registration. It is clear about the outcome but never explicitly says 'registers a new agent'; the verb 'get' is used instead of 'register'. It differentiates as the 'START HERE' step among siblings, though it does not precisely name the action.

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 clearly says to start here and suggests using list_products afterwards, giving a usage sequence. It also mentions that get_data_dictionary can be tried first if the coverage spec is wanted, offering an alternative. However, it does not explicitly state when not to use this tool or provide exclusions.

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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