get_ai_build
Get full details for a single AI or software project.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Build ID; get valid IDs from list_ai_builds |
Get full details for a single AI or software project.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Build ID; get valid IDs from list_ai_builds |
Changes observed during successful MCP inspections.
Input schema / properties / id / descriptionPrevious value: -"Build ID — get valid IDs from list_ai_builds"New value: +"Build ID; get valid IDs from list_ai_builds"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Get full details,' which implies a read operation, but it does not describe what fields are returned, how errors or missing IDs are handled, or any authentication or rate-limit considerations.
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 one concise sentence with no filler. It is front-loaded with the core action, though 'AI or software project' is slightly redundant and could have been more precise regarding what an 'AI build' is.
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 single-parameter read tool, the description is minimally sufficient: an agent knows to pass an ID and receive full details. However, with no output schema and no annotations, the vagueness of 'full details' and the absence of error/not-found behavior leave meaningful gaps.
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?
Schema description coverage is 100%, so the baseline is 3. The description itself adds no parameter-specific meaning, but the schema's id description provides useful guidance by pointing to list_ai_builds for valid IDs, which is sufficient for a single-parameter tool.
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 clear verb and resource: 'Get full details for a single AI or software project.' It indicates a single-entity retrieval operation and is distinct from list_ai_builds, though it does not explicitly differentiate from the similar-sounding get_project sibling.
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 provides no explicit when-to-use guidance or alternatives. The word 'single' implies this is for one item rather than a list, and the schema's id description references list_ai_builds, but the main description leaves the choice among get_ai_build, get_project, and list_ai_builds implicit.
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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