Get Study Overview

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond the annotations: it is a lightweight 'identity and counts only' call that deliberately excludes frozen configuration and reports, and it returns the latest revision/run/decision rather than full history. This helps an agent predict cost and scope of the call.

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 dense but well-organized: it front-loads the purpose, lists the included content in a compact series, states exclusions, and ends with a clear next-step routing. Every sentence earns its place, and the length is appropriate for the amount of useful routing information.

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 has a single required parameter, a rich output schema, and safety annotations. The description covers what the call returns, what it deliberately omits, and how to follow up. There is no missing information an agent needs to decide whether to call this tool or to interpret its scope.

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 0%, so the description must compensate for the single study_id parameter. It does so implicitly by stating the tool reads 'a whole study' and by naming the study-related entities returned. However, it does not explicitly state that study_id is the identifier to pass, nor does it give format guidance. With only one obvious parameter, the baseline is high, and the description is mostly adequate.

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 opens with a clear verb and resource: 'Read a whole study at a glance in one small call' and then enumerates exactly what is included (study, budget, recipes with latest revisions, run counts, active policies, champion summary, last decision). It also explicitly states what is NOT included ('no frozen configuration or reports'), which distinguishes it from heavier study-reading tools like get_study or list_study_recipes.

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 gives explicit usage guidance: 'Call this first, then expand exactly the recipe, run or assessment you need' and names the specific sibling tools to use next (list_study_recipes with expand, get_recipe_revision, list_study_evaluations with expand). This is a clear when-to-use and what-to-use-instead directive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.