Get Hacker News updates
hackernews_updates_getGet recently changed Hacker News item ids and usernames.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
hackernews_updates_getGet recently changed Hacker News item ids and usernames.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds that it returns item IDs and usernames, and the term 'recently changed' implies a time-bound feed. It does not contradict the readOnlyHint and openWorldHint annotations, but it doesn't clarify what 'recently' means (e.g., last hour, last day) or whether there are limits. The annotations carry the read-only safety profile, so this is acceptable but not rich.
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?
A single, clear sentence that front-loads the primary purpose. No fluff, and every word adds value.
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 zero-parameter tool with annotations covering read-only and open-world behavior, the description is sufficient: it states what is returned (IDs and usernames) and the temporal scope. It could be more specific about the time window or list format, but the overall complexity is low and nothing critical is missing.
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 tool has zero parameters, so baseline 4 applies. The description doesn't need to explain parameters, and it doesn't introduce any ambiguity.
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 states a specific action ('Get') and a clear resource ('recently changed Hacker News item ids and usernames'), so an agent can tell it's a retrieval tool. However, it doesn't explicitly differentiate from siblings like hackernews_feed_list or hackernews_item_get, relying on the name to imply the update-focused scope.
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?
There is no guidance on when to use this tool versus the many hackernews_* siblings. No mention of prerequisites, use cases, or explicit exclusions, leaving the agent to infer from the name alone.
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 is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.
All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).
The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.
The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.