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Ossie guide

ossie_guide
Read-only

Retrieve Apache Ossie semantic model reference before hand-editing models or advising ports, covering versions, object rules, expressions, Tableau mapping, validation, converters, and pitfalls.

Instructions

Reference for Apache Ossie (formerly Open Semantic Interchange, OSI), the open standard for semantic models: what it is and its versions, the object model and rules, expressions and dialects, how Tableau maps onto it, relationships, ai_context, extensions, validation, the converters for other platforms (with exact commands), and a porting playbook with pitfalls. Read it before hand-editing a model or advising on a port. topic is one of: overview, model, expressions, tableau, relationships, ai_context, extensions, validation, converters, porting; omit it for everything.

Input Schema

NameRequiredDescriptionDefault
topicNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by explaining that `topic` selects a section and omitting it returns everything, though it does not describe the output format or size.

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 front-loaded with the core purpose and ends with actionable topic/usage guidance. It is slightly repetitive because the covered topics are listed once in prose and again as the `topic` enum, but the repetition is helpful rather than wasteful.

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?

Given the output schema, annotations, and single optional parameter, the description provides everything an agent needs: what the tool is, when to use it, valid topic values, and default behavior. No important gap remains for correct invocation.

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

Parameters5/5

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

Schema description coverage is 0% and the schema has no enum, so the description carries the full burden. It compensates completely by enumerating every valid `topic` value and explicitly stating that omitting the parameter returns all topics.

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?

States a specific resource and scope: reference documentation for Apache Ossie semantic models, covering versions, object model, expressions, Tableau mapping, converters, and porting. It is clearly distinguishable from sibling operational tools such as export_to_ossie, validate_ossie, and import_from_ossie because it is explicitly a reference/read-before-editing guide.

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?

Provides a clear triggering condition: read it before hand-editing a model or advising on a port. It does not name explicit alternatives or when-not-to-use scenarios, but for a documentation tool the guidance is strong enough that an agent knows when to reach for it.

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