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AFTA certification check for a domain

verify_afta_federation

Check a domain's compliance with Agent Fair-Trade Agreement tenets by scoring its public surfaces against AFTA certification criteria.

Instructions

Calls TensorFeed's canonical AFTA certification endpoint for a domain. Returns a scored checklist of which Agent Fair-Trade Agreement tenets the domain's public surfaces satisfy. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesBare hostname, e.g. "tensorfeed.ai"
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states 'Read-only' which discloses non-destructiveness, but fails to mention authentication requirements, rate limits, or whether the endpoint can be called repeatedly without side effects.

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?

Three sentences clearly state the purpose, destination endpoint, return type, and read-only nature. No wasted words; well-structured and front-loaded.

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?

Given the simple tool with one parameter and no output schema, the description adequately explains input and output. It could mention the return format or possible error states, but it is sufficiently complete for this low-complexity case.

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?

Schema coverage is 100% for the single domain parameter, which is described as 'Bare hostname, e.g. tensorfeed.ai'. The description adds meaning by specifying it's for AFTA certification, going beyond the schema to clarify context.

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 it calls TensorFeed's AFTA certification endpoint for a domain and returns a scored checklist. It distinguishes itself from sibling tools (balance, block_number, etc.) which focus on blockchain or payment tasks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when checking AFTA certification for a domain but does not explicitly state when to use vs alternatives or provide exclusions. Context is clear but lacking 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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