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Kairos Signal — verifiable DePIN data API

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 (457 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

TDQS

A3.8/5.0
Behavior4/5

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

The description discloses key behavioral traits: the call is 'instant', requires 'no card, no human, no Stripe, ~5 seconds', and 'Nothing to cancel; credits just sit there until you spend them'. Since no readOnlyHint/destructiveHint annotations are provided, this transparency helps an agent understand side effects. It does not mention whether repeated calls grant duplicate credits, but the described behavior is otherwise clear.

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

Conciseness3/5

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

The description is front-loaded with 'START HERE' and the core value proposition, but it includes promotional tangents about live DePIN telemetry, verify_url, GPU inference, and DAG manifold that are not necessary for calling this registration tool. These details dilute focus, though the main instructions remain prominent.

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?

For a simple two-parameter registration tool with no output schema, the description covers the essential context: what the user gets (API key and $5 credits), how long it takes, what happens afterward ('list_products'), and alternatives for coverage specs. The response format is not specified, but the tool's simplicity and clear outcome make it adequately complete.

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?

The input schema already covers both parameters ('agent_name', 'email') with a helpful note on anonymous registration, so schema description coverage is 100%. The description adds no additional parameter-level meaning beyond mentioning the outcome of the call. Baseline 3 is appropriate given the schema's high coverage.

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 clearly states the tool's function: 'One call: get $5 free credits + API key' and orients it as 'START HERE', which conveys registering an agent to receive credentials and credits. It distinguishes the tool from siblings by positioning it as the onboarding entry point, though it does not explicitly say 'register an agent account'.

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 explicit sequencing and alternatives: 'START HERE', 'Try get_data_dictionary first if you want the coverage spec', and 'or GET https://kairossignal.com/try with zero setup'. It also suggests the next step 'Then list_products'. It lacks an explicit 'do not use if already registered' exclusion but still offers strong contextual guidance.

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

A3.7/5.0
Disambiguation4/5

Most tools target distinct actions (register, list, purchase, fetch, verify). The only ambiguity is between get_zk_provenance and verify_footprint, both providing cryptographic proofs, but they serve slightly different purposes (record provenance vs dataset footprint).

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern (e.g., list_datasets, purchase_data, check_balance), making the set predictable.

Tool Count5/5

10 tools is appropriate for the server's scope, covering user management, data browsing, purchasing, and verification without redundancy.

Completeness4/5

The set supports the full workflow: register, browse products/datasets, purchase, fetch data, check/top-up credits, and verify provenance. Minor gap: no way to view purchase history or account details, but core functionality is complete.

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