trend_llm_citations

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

With no annotations, the description must disclose behavioral traits. It does not mention whether the tool is read-only, requires authentication, has rate limits, or any side effects. It only describes the output format, leaving the agent uninformed about important behavioral context.

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 extremely concise: two sentences that front-load the purpose and output, then clarify the engine parameter. Every word adds value, with no fluff 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?

While an output schema exists and the description lists output columns, it lacks context on what a snapshot is, how timestamps are handled, and the limit parameter's effect. For a time-series tool, additional detail would improve completeness, but the basic functionality is conveyed.

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 coverage is 0%, so the description must compensate. It explains that engine filters to one of five specific values and that target_domain is a domain string. However, limit parameter is not mentioned, and the description does not fully cover all parameters.

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 identifies the tool's purpose: returning per-snapshot citation share for a target domain over time. It specifies the output columns and the optional engine filter, making the intent unambiguous. However, it does not explicitly differentiate from siblings like snapshot_llm_citations or multi_llm_citation_check.

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 provides no guidance on when to use this tool versus alternatives (e.g., snapshot_llm_citations for a single snapshot, list_llm_engines for available engines). No prerequisites, when-not-to-use, or context for choosing this trend tool.

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