Be Trendy

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

With no annotations provided, the description fully carries the transparency burden. It discloses the search scope (niche/keywords, not global trends), filtering behavior (removes spam/near-duplicates), output composition (scored topics, sample tweets, engagement numbers, demand signals, timing recommendation), and important guardrails (do not fabricate engagement numbers, ground claims in sample tweets). This goes well beyond a basic read-only declaration and gives the agent clear expectations.

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 longer than typical but front-loaded with the primary purpose and then systematically explains outputs and post-usage guidance. Every sentence serves a purpose, and the structure is logical (what → how → what to do next → warnings). It is slightly verbose but appropriate for a tool with no annotations or output schema, as it must convey necessary context.

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 has no output schema and no annotations, the description must explain return values and safety/behavioral aspects. It does this thoroughly: it names the specific output components (trendingTopics, painPointSignals, sample tweets, engagement numbers, timing recommendation) and explains how the results should be used, including warnings against fabrication. This makes the tool usable for an AI agent without additional external context.

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 description coverage is 100%, so the schema already documents all 6 parameters. The description adds minimal semantic value beyond mentioning 'niche/keywords' and 'product's name/description/audience' in the context of post-call content generation. It does not provide additional meaning or syntax for the parameters, so it stays at the baseline score for high schema coverage.

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: discover trending topics on X scoped to a niche, with specific verbs ('Discover', 'Searches') and a clear resource (X posts). It explicitly distinguishes itself from X's generic global trending list and from sibling tools, which are all content posting/draft/DM actions, making it unique as a trend research tool.

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 strong usage context: it is meant to be used before writing content, and explicitly instructs what to do after calling it ('use the returned trendingTopics... to write natural, platform-appropriate content'). It also notes what the tool does not do (does not generate content itself, does not use X's global trending list). However, it does not explicitly state when not to use it or name alternative tools, though no direct alternative exists among siblings.

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