Sibyl

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

With no annotations provided, the description carries full burden of behavioral disclosure. It mentions the tool 'researches the topic' but doesn't specify sources, depth, or limitations. No information about rate limits, authentication needs, or potential errors is provided, leaving significant behavioral gaps for a research-based tool.

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 efficiently structured with a clear purpose statement followed by behavioral details and parameter documentation. Every sentence adds value: the first defines the core function, the second explains the research process, and the third provides parameter examples. No wasted words or redundancy.

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?

Given the tool's moderate complexity (research + timeline generation), the description covers purpose and parameters adequately. With an output schema present, return values don't need explanation. However, the lack of behavioral details about research methodology and limitations prevents a perfect score despite good coverage of other aspects.

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?

The description adds meaningful context for the single parameter 'topic' with concrete examples ('OpenAI history', 'Canada immigration policy changes 2024-2026'), which is valuable since schema description coverage is 0%. This compensates well for the lack of schema documentation, though it doesn't explain format constraints or validation rules.

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 clearly states the tool's purpose with specific verbs ('Generate', 'Researches', 'extracts') and resources ('chronological timeline', 'key events', 'structured timeline table'). It distinguishes from siblings like 'research' (general) or 'analyze' (analytical) by focusing specifically on timeline creation with chronological ordering.

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 implies usage for topics requiring chronological event tracking, but doesn't explicitly state when to use this versus alternatives like 'research' (general research) or 'trends' (pattern analysis). No exclusions or prerequisites are mentioned, leaving some ambiguity about optimal use cases.

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