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LosslessFunction

Dataverse MCP Server

refresh_metadata_cache

Clear cached Dataverse table metadata to force fresh schema retrieval after schema changes, ensuring describe_table and list_tables return updated information.

Instructions

Invalidate cached table metadata so the next call to describe_table or list_tables fetches fresh data. Use this after schema changes (new fields, new relationships) in your Dataverse environment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableNameNoSpecific table to invalidate. Omit to clear ALL cached metadata.
Behavior4/5

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

With no annotations provided, the description carries the burden of disclosing behavior. It explains the immediate effect (next calls to describe_table or list_tables get fresh data), which is the core behavioral trait. It does not mention potential side effects like global cache clearing, but that is covered in the parameter schema. The description adds useful context beyond the schema, such as the trigger condition (schema changes).

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, front-loaded with the main action and then the usage context. Every word earns its place, with no fluff or redundant details.

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?

This is a simple tool with one optional parameter, fully documented in the schema. The description covers purpose, effect, and when to use it. There is no output schema needed for a cache invalidation operation, and the description provides enough context for an agent to decide when and how to invoke it.

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 coverage is 100%: the sole parameter tableName has a clear description ('Specific table to invalidate. Omit to clear ALL cached metadata.'). The tool description itself does not add further parameter-level meaning, so the baseline score of 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 clearly states the tool's function: invalidating cached table metadata to force fresh data on the next call to describe_table or list_tables. It uses a specific verb (invalidate) and resource (cached table metadata), and explicitly distinguishes its scope from siblings by naming the affected read operations.

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

Usage Guidelines5/5

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

The description gives explicit guidance on when to use the tool: 'Use this after schema changes (new fields, new relationships) in your Dataverse environment.' This provides a clear, actionable context for the agent, even though it does not mention alternatives (there are none for this specific cache invalidation purpose).

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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