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Zmokizmoghi

orca-profiles-mcp

by Zmokizmoghi

normalize_profile

Removes redundant keys in OrcaSlicer profiles whose values match the parent, preserving inherited settings and reducing clutter.

Instructions

Drop keys whose values are identical to the parent's

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
typeYes
forceNo
backupNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavior, but it only says keys are dropped. It does not mention that this modifies profiles in place, whether changes are reversible, what backup/force do, what happens to child profiles, or any side effects—so a mutating tool is under-disclosed.

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

Conciseness3/5

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

The sentence is grammatically tight and front-loaded with the main action, with no filler. However, it is so terse that it sacrifices necessary context about parameters and effects, making it under-specified rather than appropriately complete.

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

Completeness2/5

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

The tool has four parameters, no output schema, and no annotations, yet the description only covers the core drop behavior. It omits what 'parent' means, how force/backup alter execution, what happens to the profile, and what the result looks like, so the definition is not complete enough for reliable invocation.

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

Parameters1/5

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

Schema description coverage is 0%, and the description mentions none of the four parameters: name, type, force, or backup. It does not explain how these parameters affect the normalization behavior, leaving the agent to guess.

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 gives a specific verb ('drop') and the object ('keys whose values are identical to the parent's'), which clearly conveys a normalization/removal operation and distinguishes it from sibling tools like get_profile or delete_profile. However, it never explicitly names 'profile' or defines what 'parent' refers to, so a bit of inference is required.

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?

No guidance is provided about when to use normalize_profile versus alternatives such as diff_profiles, check_deltas, or compare_with_upstream. The use case is only implied by the operation described, with no explicit context or exclusions.

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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