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miroslawfranek

Open-E JovianDSS REST API Documentation MCP Server

get_edss_documentation_enhanced

Retrieve Open-E JovianDSS REST API documentation with automatic version discovery and jQuery processing to reveal hidden content for integration and endpoint analysis.

Instructions

Get EDSS documentation with automatic version discovery and jQuery processing

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
versionNoVersion: 'latest', 'trunk', or specific release namelatest
apiVersionNov4
useJavaScriptNoProcess with jQuery to reveal hidden content
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'automatic version discovery' and 'jQuery processing', which hint at some automation and content processing, but doesn't describe what 'discovery' entails (e.g., fallback logic), what 'hidden content' means, performance implications, error handling, or authentication needs. This leaves significant gaps for a tool with processing capabilities.

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 a single, efficient sentence that front-loads the core purpose ('Get EDSS documentation') and immediately specifies key enhancements. Every word earns its place with no redundancy or unnecessary elaboration, making it easy for an agent to parse quickly.

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?

Given 3 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., raw HTML, processed content, metadata), how errors are handled, or the scope of 'documentation' (e.g., API docs, user guides). For a tool with processing logic and multiple parameters, more context is needed to guide effective use.

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 67% (2 out of 3 parameters have descriptions). The description adds minimal value beyond the schema: it implies 'version' parameter relates to 'automatic version discovery' and 'useJavaScript' relates to 'jQuery processing', but doesn't explain how these interact or provide additional context. With moderate schema coverage, this meets the baseline but doesn't compensate for gaps.

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 verb ('Get') and resource ('EDSS documentation'), and specifies two key capabilities: 'automatic version discovery' and 'jQuery processing'. However, it doesn't explicitly differentiate from sibling tools like 'get_edss_documentation' (without 'enhanced'), leaving some ambiguity about what makes this version 'enhanced'.

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 provides no guidance on when to use this tool versus alternatives like 'get_edss_documentation', 'download_edss_documentation', or 'search_edss_documentation'. It mentions capabilities but doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage context.

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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