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Glama

get_study

Retrieve a study's design summary, cumulative reservations, and aggregate final evidence for review.

Instructions

Read study design summary, cumulative reservations and aggregate final evidence.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "study_id": "<study_id>"
    },
    "name": "get_study"
  }
}

Input Schema

NameRequiredDescriptionDefault
study_idYes
target_limitNo
target_offsetNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full load, and "Read" only weakly implies a safe read-only operation. It says nothing about whether the reserved/evidence sections are scoped by caller permissions, whether missing evidence is omitted or null, or that results are paginated via target_limit/target_offset — a notable omission given the two pagination parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with the verb first and no filler. It is efficient, though the brevity edges toward under-specification rather than tightness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value detail is legitimately deferred, and the complexity is low. Still, the pagination behavior and the tool's place among the many get_study_* siblings are left unexplained, which is the minimum an agent needs to pick it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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, and it does not explain any of the three parameters. study_id is self-evident, but "target_limit"/"target_offset" are ambiguous — the description never says what a "target" is (presumably a reservation) or that these paginate that collection.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Read" plus three named resources (design summary, cumulative reservations, aggregate final evidence) tells an agent concretely what comes back, which distinguishes it from case/attempt/sample siblings. It stops short of explicitly saying how it differs from get_study_assessment or get_study_case_spec, so no sibling routing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance: nothing says whether this is the top-level overview to call before drilling into get_study_cases or get_study_attempt, and no prerequisites or exclusions are stated. The agent must infer its role in the family from the name alone.

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