Read or replace a dataset's complete business definitions from supplied JSON, merging existing definitions first, without persisting changes or rewriting SQL.
Read business definitions, or replace the COMPLETE session definition with supplied JSON. Read and merge existing definitions first. Does not persist definitions or rewrite SQL.
| Name | Required | Description | Default |
|---|---|---|---|
| datasetId | Yes | ID returned by ava_source in this MCP connection | |
| definition | No |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only supply openWorldHint=false and destructiveHint=false; the description adds the crucial context that the tool does not persist definitions and does not rewrite SQL, which explains why the replace is non-destructive. It also warns that supplied JSON replaces the COMPLETE definition, a real data-loss hazard an agent must know before calling.
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?
Three short, front-loaded sentences with no filler, and the read/replace duality leads. The phrasing 'COMPLETE session definition' is emphatic but slightly cryptic about where that session definition lives.
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 two-parameter tool with a nested free-form object and no output schema, the description covers mode selection, safety boundaries, and the merge precondition adequately. It leaves gaps on what a read returns, whether definitions are per-dataset or connection-wide, and what happens to unrelated keys during a replace.
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 coverage is 50%: datasetId is documented in the schema, while the nested definition object is not. The description partially compensates by establishing that the passed JSON must be complete because it replaces rather than patches, but it says nothing about the object's expected structure or keys.
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+resource pair, 'Read business definitions, or replace the COMPLETE session definition', and names the data being manipulated. It stops short of differentiating from ava_schema or ava_query, so an agent cannot fully tell from the text alone which tool owns which kind of metadata.
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?
It gives one concrete workflow instruction, 'Read and merge existing definitions first', which implies read-then-replace ordering. It never says when to choose this over ava_schema for inspecting a dataset, nor when a read is sufficient versus a replace.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.