What Hacker News said about a topic: matching stories with points, comment counts and links to the threads, plus aggregates — total matches, points and comments returned, most-submitted domains, and when it was first and last discussed. Price: $0.004
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | Ranking (default relevance) | |
| limit | No | Stories to return (default 10) | |
| query | Yes | What to search Hacker News for |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It details the output contents (stories with points, comments, links, aggregates) and price, but does not explicitly state that it is a read-only operation, nor does it mention rate limits or other constraints. It gives useful but incomplete transparency.
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 at two sentences and front-loads the core purpose. The first sentence packs relevant detail about outputs and aggregates, and the second adds pricing. No fluff, but slightly dense phrasing prevents a perfect score.
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?
For a simple search tool with no output schema or annotations, the description covers the main purpose, output structure, and pricing. It lacks explicit notes on read-only status or edge-case behavior, but overall it provides enough context for an agent to invoke the tool appropriately.
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 schema has 100% coverage for all three parameters, including descriptions for query, sort, and limit. The description adds general context about the tool's output but does not enhance understanding of the parameters themselves, so it aligns with the baseline for full 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 states the tool's function: searching Hacker News discussions for a topic. It specifies the resource (Hacker News) and the action (search), and distinguishes it from sibling search tools like search_news and search_web by focusing on discussions and aggregates.
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 when to use the tool (when you want HN discussions), but it does not explicitly mention alternatives or state when not to use it. The context is clear from the wording, but lacks direct guidance.
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.
Several tool clusters have near-overlapping purposes: fetch_webpage/fetch_webpage_pro/fetch_resilient and batch_fetch/get_contents are hard to distinguish, and answer_question/research/deep_research differ mainly in price and depth. The search_* and intel_* families are clearer, but the core fetching and research overlap creates ambiguity.
Most tools follow a verb_noun snake_case pattern (fetch_webpage, search_web, extract_data), but there are notable exceptions like domain_intel, package_intel, youtube_transcript, memory_set, and intel_company, where the prefix/suffix convention is inconsistent. Still, the naming is broadly readable.
35 tools is a large surface, far beyond the typical 3-15 range. The server covers many research verticals, but the number feels bloated, especially with multiple fetch and research variants that could be consolidated.
The tool set covers a wide range of web research needs: searching, fetching, crawling, extracting, screenshots, domain/tech/package intelligence, and market/competitive analysis. It lacks obvious lifecycle operations for monitors (list/delete/update) and memory (get/delete), but core workflows are well covered.