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server_refresh_metadata

Refresh runtime metadata for registered tools without re-registering them, ensuring the latest definitions are available to AI clients while minimizing disruption to editor workflows.

Instructions

Refresh runtime metadata that can safely update without re-registering Python tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It only notes that the update is 'safe' and avoids re-registration, but does not disclose side effects, idempotency, or what metadata is affected. The dry_run parameter suggests a preview mode that is not explained.

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 a single, front-loaded sentence with no filler. It communicates the core purpose efficiently, though it sacrifices detail for brevity.

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?

With no parameter explanation and no behavioral detail beyond a safety hint, the description is incomplete for an agent. The presence of an output schema helps but does not compensate for the missing parameter semantics and usage context.

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

Parameters1/5

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

Schema coverage is 0% and the description does not mention the single 'dry_run' parameter at all. The agent has no way to know what this boolean controls or why it defaults to true, which is a critical gap for a tool with only one parameter.

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?

States a clear verb ('refresh') and resource ('runtime metadata'), and adds a distinguishing clause ('without re-registering Python tools') that hints at its non-destructive nature. It is distinct from sibling server tools like status or diagnostics, though it does not explicitly name any alternative.

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?

No guidance on when to use this tool versus siblings such as server_operation_status or server_lifecycle_status. The description implies it is for refreshing metadata safely but gives no conditions, triggers, or exclusions, leaving the agent to infer usage.

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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