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Agentic Fabrication Network (AFN)

A shop's stocked sheet gauges

get_shop_gauges

Every sheet thickness (gauge) ONE named shop stocks right now, per material — read live off the shop's declared catalog, no quote needed. Call it when the user asks what thicknesses/gauges a specific maker carries ("what thicknesses does SendCutSend have in mild steel?"). For the whole network's ladder use get_network_capabilities instead. Never answer a gauge question from memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
shopYesThe shop as the user or the offer cards name it ("SendCutSend", "sendcutsend")
materialNoAdvisory: narrow the relayed list to one material ("mild steel", "5052")

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It clearly states this is a live read off the declared catalog, that no quote is needed, and that answers must not come from memory — which conveys freshness and non-mutating behavior. It could add failure/auth details, but the most important behavioral traits are disclosed.

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 dense sentences with no filler; the core behavior and scope appear first, usage guidance second, and the alternative tool third. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter lookup with no output schema, the description explains what is returned ('every sheet thickness per material'), how current it is, and when to use it versus the alternative. Nothing essential for invoking the tool correctly is missing.

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%, so the baseline is 3, and the description adds meaningful context: it clarifies that the shop name is matched flexibly as the user or offer cards name it, and that material is an advisory narrowing filter rather than a hard requirement. This helps the agent map user phrasing to parameters beyond what the schema alone provides.

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 names a specific action — returning the sheet thicknesses a single named shop currently stocks — and identifies the targeted resource ('ONE named shop' vs. the whole network). It clearly differentiates from sibling get_network_capabilities by scope, so an agent can select it confidently.

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

Usage Guidelines5/5

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

The description gives an explicit when-to-use trigger ('Call it when the user asks what thicknesses/gauges a specific maker carries') and routes the network-wide aggregate case to get_network_capabilities. It also warns against answering from memory, providing actionable 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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