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compare_timelines

Compare research timelines across multiple topics to analyze drug development progress or research evolution side by side.

Instructions

Compare research timelines of multiple topics.

Useful for:

  • Comparing drug development timelines

  • Contrasting research evolution across conditions

  • Understanding parallel research tracks

Args: topics: Comma-separated topics to compare Example: "remimazolam,propofol,dexmedetomidine" max_events_per_topic: Maximum events per topic

Returns: Comparative analysis of the timelines.

Example: compare_timelines("remimazolam,propofol", max_events_per_topic=10)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicsYes
max_events_per_topicNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It mentions that the tool returns a 'Comparative analysis' but does not specify whether the tool is read-only, what side effects exist, or any authentication or rate limit requirements. This lack of transparency is a notable gap.

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?

The description is well-structured with clear sections (description, useful for, args, returns, example). It is concise and avoids redundancy, though the bullet list could be tighter. Every sentence contributes value.

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

Completeness4/5

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

Given that an output schema exists, the description does not need to detail return values. It provides sufficient context for the two parameters and an example. However, it could mention the type of output (e.g., comparison table) to further aid the agent.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description compensates by explaining the 'topics' parameter as 'Comma-separated topics to compare' with an example, and 'max_events_per_topic' as 'Maximum events per topic'. This adds meaning beyond the schema's basic type info.

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

Purpose5/5

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

The description clearly states 'Compare research timelines of multiple topics' and provides specific examples like comparing drug development timelines. This verb+resource combination is precise and distinguishes the tool from siblings such as 'build_research_timeline' and 'analyze_timeline_milestones'.

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

Usage Guidelines4/5

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

The description includes a 'Useful for' section listing concrete scenarios (e.g., comparing drug development timelines). While it does not explicitly state when not to use the tool or name alternative tools, the context is clear enough for an AI agent to infer appropriate use cases.

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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