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DataCraftsmanAU

DataCraftsmanAU/vineverse-mcp

Bundle log and generation time

get_changelog
Read-onlyIdempotent

Inspect the knowledge base's changelog to see when data was ingested, determine currency, and cite a version. Use bundleGenerated for data versioning; get_stats tracks process restarts.

Instructions

The knowledge base's own log file, plus when the data was actually ingested. Use bundleGenerated to answer "how current is this" or to cite a version — the generated field on get_stats is when this server built its in-memory index and changes on every restart, which is a fact about the process rather than the data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
logYes
urlYes
noteNo
licenceNo
indexBuiltYes
okfVersionNo
bundleGeneratedNo
Behavior3/5

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

Annotations already cover readOnly, idempotent, and non-destructive behavior, so the description doesn't need to restate safety. It adds useful semantic context about the time fields and how they differ from get_stats, but it does not disclose other behavioral traits such as pagination, volume of log data, or any potential rate limits. The context added is helpful but modest.

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 tightly packed sentences say exactly what the agent needs. The first sentence states what is returned; the second gives a sharp use case and contrasts with the sibling tool. No redundancy, no filler, and the guidance is front-loaded.

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 that there are no parameters, the presence of an output schema, and annotations covering the safety profile, the description supplies the remaining critical context: what bundleGenerated means, how to use it, and why get_stats's generated field is not equivalent. There is no missing information that would prevent a competent agent from invoking take this tool correctly.

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

Parameters4/5

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

There are 0 parameters, and the schema description coverage is 100% by default, so the parameter baseline is 4. The description does not need to compensate beyond that, and it instead correctly spends effort on clarifying the output field semantics.

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 identifies the resource returned — the knowledge base's own log file and actual ingestion time. It distinguishes the tool from get_stats by contrasting `bundleGenerated` with the `generated` field, so an agent can tell them apart. It lacks an explicit verb like 'returns' or 'provides', but the intent is unmistakable.

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 explicitly directs when to use this tool: 'Use `bundleGenerated` to answer how current this is or to cite a version.' It also directly names get_stats as an alternative and explains why its `generated` field is not the right source for data recency. This is clear when-and-when-not guidance.

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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