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josecarlos3390

SAP HANA MCP Server

Read knowledge case

hana_read_kb_case
Read-onlyIdempotent

Fetch complete Markdown case content from local or remote knowledge base by filename, ensuring access even offline or with expired license.

Instructions

Read the full Markdown content of a local or remote knowledge base case by filename. Available even in offline mode when the license is expired.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filenameYesCase filename (e.g. 2025-07-06-protocol-issue.md)
Behavior4/5

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

While annotations already indicate readOnly, idempotent, and non-destructive traits, the description adds useful behavioral context: it retrieves 'full Markdown content', supports 'local or remote' cases, and works offline even with an expired license. No contradictions with annotations.

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?

Two sentences, no redundancy, front-loaded with the primary purpose. Every phrase adds value: 'full Markdown content', 'local or remote', and 'offline mode when license expired' are all informative without being verbose.

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

Completeness4/5

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

For a simple one-parameter tool with no output schema, the description covers the core operation and return content type ('full Markdown content'). The offline availability and local/remote scope add context. It could mention error scenarios or whether the content is wrapped in a JSON response, but overall it is sufficiently complete for an AI agent.

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?

The schema already covers the single parameter with a clear example. The description mentions 'by filename' and 'local or remote' but does not add significant new meaning beyond the schema. The parameter semantics are adequately handled by the schema, so a baseline 3 is appropriate.

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?

The description specifies the exact action ('Read the full Markdown content'), the target resource ('local or remote knowledge base case'), and the key input ('by filename'). It clearly distinguishes from sibling tools like hana_search_knowledge_base (search) and hana_save_knowledge_case (write).

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 provides situational context—'Available even in offline mode when the license is expired'—which signals when this tool is particularly useful. However, it does not explicitly state when not to use it or mention alternatives, so it falls 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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