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Erryb95

aras-plm-mcp

by Erryb95

aras_get_revisions

Retrieve the complete revision history of any versionable Aras item, showing every generation with revision, state, lock owner, and current flag instead of only the current revision.

Instructions

Storia completa delle revisioni di un elemento versionabile: tutte le generazioni con revisione, stato, chi la tiene bloccata e quale e' la corrente. In Aras le generazioni sono righe distinte con id diversi che condividono config_id, e una query normale restituisce solo quella corrente: qui le vedi tutte.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesid di una qualsiasi generazione
itemTypeYeses. 'Part', 'Document'
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does a good job: it discloses that the tool returns all generations, not just the current one, and lists the fields shown (revision, state, lock holder, current). It also explains the config_id sharing mechanism, which helps the agent understand what the result represents. It does not explicitly state read-only safety or error/authorization behavior, but the read-oriented nature is strongly implied.

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 two sentences, with the main purpose front-loaded and the supporting Aras domain context in the second sentence. Every sentence earns its place, with no wasteful filler.

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?

The description gives a solid high-level view of the tool's behavior and its Aras data-model context, but with no output schema and no annotations, some important details are missing: the exact response shape, ordering of revisions, behavior for non-versionable items, and permission requirements. It is adequate for basic invocation but not fully complete.

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, but the description adds value by explaining that generations are distinct rows sharing config_id and that a normal query returns only the current generation. This clarifies that the id parameter can be any generation's id, which goes beyond the schema's one-line description.

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 clearly states the tool returns the complete revision history of a versionable item, including revision, state, lock holder, and current revision. It distinguishes itself from a normal Aras query that returns only the current generation, but it does not explicitly differentiate from sibling tools like aras_get_history or aras_get_item, so it stops short of a 5.

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?

The description gives clear context on when to use the tool: when you need all generations rather than only the current one. It explains the Aras generation model and contrasts the behavior with a normal query, but it does not explicitly name alternatives or state exclusions, so usage guidance is strong but not fully explicit.

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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