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AXIOVEX

Manufacturing Inference Advisor MCP

by AXIOVEX

analyze_inference_project_tool

Read-onlyIdempotent

Estimate a transparent capacity envelope for AI inference deployments from model, context, concurrency, and growth inputs to enable accurate capacity planning.

Instructions

Estimate a transparent capacity envelope from the model, context, concurrency and growth inputs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, signaling a safe read-only operation. The description adds the specific focus and inputs, but does not disclose additional behavioral traits such as whether it returns a numeric range or a structured estimate, or whether it uses heuristics. However, given the annotations, the description is not misleading, and the extra context about inputs is useful.

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

Conciseness4/5

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

The description is a single sentence, concise and front-loaded with the primary action ('Estimate a transparent capacity envelope'). It lists the key inputs without unnecessary detail. It could be argued it is slightly under-specified regarding usage, but what is written is efficient and clear.

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

Completeness3/5

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

Given the tool has an output schema and simple parameter (a single 'project' object), the description covers the essential purpose and inputs. However, the lack of guidance on when to use it, and the opaque 'project' parameter structure, leave room for improvement. The description is adequate for a basic understanding but not comprehensive.

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 description coverage is 0%, so the schema provides no semantics for the single parameter 'project'. The description mentions the relevant fields (model, context, concurrency, growth), which partially compensates, but it does not explain the structure or expected format of the 'project' object. With only one parameter, the baseline for requiring description compensation is moderate, and the description provides some value.

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 states a specific verb ('Estimate') and resource ('capacity envelope'), and mentions the key inputs (model, context, concurrency, growth). It clearly indicates the tool performs an analysis. However, it does not explicitly distinguish it from siblings like 'assess_existing_infrastructure_tool' or 'recommend_architecture_tool', though the 'capacity envelope' focus helps.

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

Usage Guidelines2/5

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

The description gives no explicit guidance on when to use this tool versus alternatives. The sibling list includes 'assess_existing_infrastructure_tool' and 'recommend_architecture_tool', but no conditions are given to select between them. The context hints that it analyzes inputs, but when to choose it over others is left entirely to inference.

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