Read current Data Window values for all studies or one exact entity.
Read current Data Window values for all studies or one exact entity.
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | No | ||
| target_id | No | Exact Chrome tab target ID from browser_list_tabs. Required for changes. | |
| expected_layout_id | No | Expected saved-layout ID. A mismatch stops the operation before writing. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered structurally. The description adds that this reads current values and can target all studies or one exact entity, but it does not disclose return behavior, pagination, or any operational constraints beyond what annotations and schema already provide.
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 a single front-loaded sentence with no filler. The read action and scope are immediately clear.
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?
The tool is a read-only operation with three optional parameters and no output schema. Annotations and schema cover much of what an agent needs, but the description leaves gaps around what a Data Window value is, what happens when entity_id is omitted, and what shape the result takes.
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 67%, with descriptions for target_id and expected_layout_id but none for entity_id. The phrase 'one exact entity' gives some meaning to entity_id, but the description does not explain the relationship between entity_id, target_id, and expected_layout_id. Baseline 3 is appropriate given partial schema coverage.
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 gives a specific verb and resource: reading current Data Window values. It also states the scope, all studies or one exact entity. It does not explicitly distinguish itself from nearby data_* siblings, but the resource is concrete enough to identify the tool.
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?
Usage is implied by 'Read current Data Window values' and the all-studies versus one-entity scope. There is no explicit when-to-use guidance, no exclusions, and no named alternatives such as other data retrieval tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.