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List Hacker News user submissions

hackernews_user_submissions_list
Read-only

List a Hacker News user's stories, polls, and jobs (newest first). Accepts a username. Returns a list (use page/pageSize when paginated).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoZero-based page index (maximum 50 pages, up to 1,000 hits).
limitNoHits per page (1–50). Default: 20. Prefer this over `pageSize`.
pageSizeNoDeprecated alias for `limit`. When both are set, `limit` wins.
usernameYesHacker News username (case-sensitive).

TDQS

A3.9/5.0
Behavior4/5

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

While annotations declare readOnlyHint=true and openWorldHint=true, the description adds meaningful behavioral facts: it lists specific content types (stories, polls, jobs), sorting order (newest first), and pagination hints (use page/pageSize). This goes beyond the safety profile conveyed by annotations and gives the agent useful operational expectations. It does not discuss error handling or rate limits, but that is minor given the simple read-only nature.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficient: three short sentences deliver the core purpose, content scope, and pagination hint with minimal fluff. The main action is front-loaded. It loses a point for using 'page/pageSize' instead of the schema-preferred 'limit', which introduces slight imprecision, but overall it is well-structured and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only list tool with no output schema, the description covers the essential operational aspects: what is returned, order, and pagination. It does not detail the exact return structure, but that is expected without an output schema. The lack of explicit comparisons to sibling tools is a minor gap, but overall the information is sufficient for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3; the description adds no additional meaning beyond what the schema already provides for parameters. It mentions 'page/pageSize' but omits the preferred 'limit' parameter, and slightly conflicts with the schema's deprecation note on pageSize. It does not clarify or enrich parameter usage, so it neither adds value nor detracts significantly, staying at the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('List') targeting a clear resource: a Hacker News user's 'stories, polls, and jobs' with a defined order ('newest first'). This distinguishes it from sibling tools like hackernews_user_comments_list or hackernews_user_favorites_list by naming the content types explicitly. The purpose is unambiguous and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by naming the resource type (stories, polls, jobs) but does not explicitly contrast with alternatives. It never says 'use this for submissions, not comments' or mentions sibling tools. The differentiation relies on the tool name and sibling naming patterns rather than explicit guidance, so it meets the 'implied usage' level but not a clear 'when/when-not' directive.

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

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TDQS

B3.4/5.0
Disambiguation5/5

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.

Naming Consistency5/5

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.).

Tool Count2/5

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.

Completeness4/5

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.