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Mesteriis

Plasticity MCP

plasticity_combine_material_coupon_data

Combine 2–8 compatible immutable material coupon records for one exact print process into a new record for exact-process matching and FEA binding, rejecting conflicts without averaging.

Instructions

Explicitly consolidate 2–8 compatible immutable physical coupon records for one exact single-material print process. It combines only non-conflicting measured properties and their source evidence; it never averages or infers values. Supply specimenCount as the caller-confirmed number of unique physical specimens across all source records. The result is a new immutable record with composedFromRecordIds, and can be used for exact-process matching and FEA binding. Different processes, conflicting values or print frames are rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recordIdsYes
specimenCountYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare a non-destructive write in a closed world; the description adds substantive semantics beyond that: it never averages or infers values, only non-conflicting properties are merged, conflicts cause rejection, and the output is a new immutable record carrying composedFromRecordIds. These are behavior rules an agent could not infer from the schema or annotations.

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?

Dense but front-loaded, leading with the action and its scope before the specimenCount instruction and the outcome. Five sentences is close to the useful maximum; a sentence explaining FEA/exact-process reuse is informative but the most expendable.

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?

With no output schema, the description still states the return value (a new immutable record with composedFromRecordIds) and the usable downstream purposes. Combined with the rejection rules and the specimenCount explanation, nothing essential for a correct call 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 description coverage is 0%, so the description must carry the load: it explains that specimenCount is the caller-confirmed count of unique physical specimens across all source records, which the schema only types as an integer. It also conveys that recordIds is a set of 2–8 coupon identifiers to be merged, though it leaves the id format to the schema pattern.

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?

Names a specific verb+resource ('consolidate ... coupon records') and pins the scope with hard constraints: 2–8 records, one exact single-material print process. This is clearly distinguishable from sibling operations such as match_/list_/record_material_coupon_data, which do not merge records.

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

Usage Guidelines4/5

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

Gives explicit preconditions for use (compatible immutable coupon records, single material, single print process) and names rejection cases (different processes, conflicting values, differing print frames). It does not explicitly route the agent to an alternative sibling when those preconditions fail, so it stops short of a 5.

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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