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ottonic
by ottonic

Manufacturing Process Limits

process_limits

Describe geometric feasibility limits for a manufacturing process—wall thickness, hole distances, radii, draft angle, and pocket ratios—to test measured features for manufacturability.

Instructions

Describe what a manufacturing process can hold: minimum wall thickness, minimum hole-to-edge and hole-to-bend distances, minimum internal corner radius, bend radius, draft angle, pocket depth-to-width ratio. Call process_feasibility to test one measured feature against these. These are published rules of thumb for geometric feasibility, not a specific shop's capability, and they say nothing about cost or lead time.

Input Schema

NameRequiredDescriptionDefault
processYesWhich process to describe.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose important behavioral context: results are generic published rules of thumb, not shop-specific capability, and contain no cost or lead-time information. It stops short of explicitly stating that the tool is read-only or side-effect-free, but the descriptive verb and scope caveats make the behavior largely clear.

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 front-loaded with the tool's purpose, efficiently lists the returned limit types, then adds the alternative and scope caveats in two compact sentences. Every sentence earns its place.

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 one-parameter lookup with an output schema, the description is largely complete: it explains what is returned, clarifies scope, and routes the agent to process_feasibility. A minor gap is that it does not mention the sibling process_list as a way to discover valid process names, but overall the agent has enough to call it correctly.

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%, so the single 'process' parameter is already documented in the schema. The description does not add syntax, examples, or valid process-name guidance beyond the schema, so the baseline of 3 applies.

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 uses a specific verb ('Describe') and clearly states the resource: geometric limits of a manufacturing process (wall thickness, hole distances, bend radius, draft angle, etc.). It also distinguishes this tool from process_feasibility, which is for testing a single measured feature, so an agent can tell the two apart without opening schemas.

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?

It explicitly names process_feasibility as the alternative for testing a measured feature, and it sets exclusions: these are published rules of thumb, not a specific shop's capability, and say nothing about cost or lead time. That gives clear when-to-use and when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.