get_experiment
Get experiment details with results Anonymous preview is limited to agentanalytics-demo synthetic read-only data; sign in for your own projects.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Experiment ID |
Get experiment details with results Anonymous preview is limited to agentanalytics-demo synthetic read-only data; sign in for your own projects.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Experiment ID |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), so the bar is lower. The description adds real context beyond that: anonymous access is restricted to agentanalytics-demo synthetic read-only data, and signing in is required for real projects. That is a meaningful auth/data-scoping disclosure, though it says nothing about pagination or result size.
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 purpose is front-loaded, but the description is a run-on with no separator between the functional sentence and the preview/auth note ("...with results Anonymous preview..."), which reads as two sentences accidentally concatenated. Size is small, but the structure cost is real.
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 one-parameter getter with no output schema, the definition covers the operation and the environment limitation. The absence of an output schema means return values need not be described, though "with results" is only a hint about what comes back. Adequate for the tool's complexity.
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?
Single required parameter with 100% schema description coverage, so the schema already documents "id". The description adds nothing about id format or where to obtain it (e.g., from list_experiments). Baseline 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?
States a clear verb+resource pair ("Get experiment details with results") that separates it from create_experiment, update_experiment, delete_experiment, and list_experiments by implying a single-item detail fetch. It does not explicitly name a sibling or contrast scope, so it stops short of a 5.
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?
There is no guidance on when to call this versus list_experiments or get_project_context. The only conditional information is an environment/auth caveat about the anonymous preview, which is not usage routing. An agent must infer that a single id yields one experiment.
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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