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Glama

Research Agent by Nova (CIVAI)

research__conduct-deep-research

Conduct deep, iterative research on a topic by generating multiple search queries, processing the results, and recursively exploring new research directions.

Input Schema

NameRequiredDescriptionDefault
depthNoDepth of recursive exploration (0-2)
topicYesThe main topic or question to research
breadthNoNumber of search queries per research direction (1-5)
objectiveYesThe specific goal or objective of the research
connection_idNoOptional connection ID for the user
max_total_queriesNoMaximum number of search queries to process (2-5)
max_duration_secondsNoMaximum duration for the research process in seconds (60-300)

Schema Changelog

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TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the iterative/recursive nature, which signals long-running, potentially expensive execution and explains the duration and query caps in the schema, but it says nothing about permissions, the connection_id requirement, cost, or failure modes.

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

Conciseness5/5

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

A single well-formed sentence that front-loads the core purpose and then explains the mechanism. Nothing is padded or redundant.

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?

The tool is complex (7 parameters, no output schema, no annotations) and the description leaves the return value entirely unspecified even though no output schema exists to cover it. The agent knows what the tool does procedurally but not what it yields or how results are shaped.

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 100%, and each parameter (depth, breadth, max_total_queries, max_duration_seconds, connection_id) is documented with ranges and defaults in the schema. The description adds no parameter-level meaning beyond what the schema already provides, so the baseline of 3 applies.

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?

The description gives a specific verb (conduct) and resource (deep, iterative research) and even explains the mechanism: generating multiple queries, processing results, and recursing. It is clearly a research-execution tool, but it never contrasts itself with the sibling research__generate-research-report, so an agent must infer the boundary.

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?

No when-to-use guidance, no prerequisites, and no mention of the natural alternative, research__generate-research-report (report vs. raw research). The agent gets a description of the mechanism but no instruction on when this tool is the right choice.

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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