What the marketing/growth niche is SAYING about one topic right now: chatter volume, who's covering it, score spread, and the top takes. Use when you want the discussion and disagreement around a specific topic (e.g. 'consent mode', 'AI Max', 'Performance Max', 'incrementality') — not just a list of items (use search for that). Args: topic (free text), since_days (default 30).
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | ||
| since_days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It effectively describes the output (chatter volume, who's covering, score spread, top takes) and notes parameter details. However, it does not explicitly state that the tool is read-only or mention any side effects, rate limits, or authorization requirements. Nonetheless, the description is informative and suggests a safe read operation.
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 concise, consisting of three well-structured sentences. It front-loads the purpose and provides examples and usage guidance without unnecessary words. Every sentence contributes to understanding the tool.
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 relative simplicity (2 parameters, no nested objects, no output schema), the description adequately explains the return values (chatter volume, who's covering, score spread, top takes). It does not discuss pagination or response size, but for a pulse tool the response is likely a single summary. Overall, it provides sufficient context for an AI agent.
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 meaning beyond the input schema: it explains 'topic' as free text with examples, and 'since_days' with a default of 30. While schema coverage is 0%, the description compensates by clarifying the purpose and usage of parameters. It could be more specific about the 'since_days' unit or expected format, but overall it adds value.
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 function: providing discussion and disagreement around a specific topic in the marketing/growth niche, including specific metrics (chatter volume, who's covering, score spread, top takes). It uses specific verbs and resources and distinguishes from sibling tools like 'search' which offers a list of items.
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 explicitly states when to use the tool ('Use when you want the discussion and disagreement around a specific topic') and when not to use it ('not just a list of items — use search for that'). It provides concrete topic examples, giving clear context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a uniquely identifiable purpose: coverage checks answering capability, get_item retrieves a single item, search handles queries, topic_pulse explores discussion around a topic, trending shows rising topics, and whats_new provides the freshest items. No ambiguity between them.
All tools follow a consistent 'earlywire_' prefix and use descriptive, lowercase snake_case names (coverage, get_item, search, topic_pulse, trending, whats_new). The naming pattern is uniform and predictable.
With 6 tools, the server is well-scoped for a marketing/growth intelligence niche. It provides essential operations without being too sparse or overloaded. Each tool contributes to a coherent workflow.
The tool surface covers the full lifecycle of interacting with the curated intelligence: discovery (trending, whats_new), search (search), deep dive (get_item, topic_pulse), and scope checking (coverage). No obvious gaps for a read-only intelligence service.
