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Kairos Signal — verifiable DePIN data API

list_products

Browse all purchasable products with prices in credits ($1 = 1 credit). Includes DePIN supply-telemetry data, signal feed tiers ($9.99-$399.90/mo), DAG manifold API ($2.99-$9.99/mo), GPU compute, and MCP unlimited access. Call after register_agent to see what to buy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It doesn't explicitly state that browsing is read-only, nor does it mention authentication requirements, pagination, or return format. The pricing context is useful but insufficient for full transparency.

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 sentences, front-loaded with the core purpose, and then provides examples and a usage hint. Every sentence adds value with no redundancy, making it both concise and well-structured.

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 parameterless listing tool, the description covers the content, pricing, and when to call it. The lack of an output schema means return-format details are missing, but the tool's simplicity and the concrete examples make it adequately complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is nothing to explain. The baseline score for 0-parameter tools is 4, and the description adequately describes the tool's behavior without needing parameter details.

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 function: 'Browse all purchasable products with prices in credits'. It provides a list of example product categories, making it unmistakable what the tool does. This distinguishes it from sibling tools like list_datasets or purchase_data.

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 an explicit usage cue: 'Call after register_agent to see what to buy.' This establishes when to use the tool. It also enumerates included product types, helping agents understand relevance. However, it doesn't explicitly contrast with alternatives like purchase_data or check_balance.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

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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