gvt_get_oldest_listGet the oldest baseline test snapshots for a batch of URLs (up to 100) in a single call. Ideal for monthly/periodic batch comparisons: fetch baselines in bulk here, then call gvt_get_latest per URL. Each result includes the URL and its oldest test object (null if no test exists for that URL).
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | Array of URLs to look up (max 100). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds concrete behavioral detail about the result shape ('Each result includes the URL and its oldest test object (null if no test exists for that URL)'), which goes beyond the schema. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long with no filler. The first sentence states action and limits, the second provides the ideal usage scenario and workflow, and the third specifies the result format. It is tightly packed and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a batch read tool, this is complete: it specifies what it does, the batch limit, why to use it, the result structure (including null behavior), and how it fits with sibling tools. No output schema exists, but the description compensates by describing the result. An agent can correctly decide to call it and understand the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'urls' is fully covered by the schema (type array, minItems 1, maxItems 100, with a description). The tool description does not add extra parameter-specific detail (e.g., URL formatting) beyond what the schema provides. Since coverage is 100%, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb (Get), resource (oldest baseline test snapshots), scope (batch of URLs up to 100), and explicitly distinguishes from the singular sibling gvt_get_oldest by noting 'in a single call'. It also references gvt_get_latest as the complementary tool, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use it ('Ideal for monthly/periodic batch comparisons') and gives a specific workflow ('fetch baselines in bulk here, then call gvt_get_latest per URL'). This clearly guides an agent away from using this tool for single-URL lookups, which are better served by gvt_get_oldest.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.