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hn_explain

Explains Hacker News terms, culture, and conventions to help users understand community-specific concepts like karma, flagged posts, and Show HN submissions.

Instructions

Get explanations of Hacker News terms, culture, and conventions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termYesHN term or concept (e.g., "karma", "flagged", "dupe", "Show HN", "Ask HN")
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Get explanations,' which implies a read-only operation, but doesn't clarify aspects like response format, potential rate limits, error handling, or whether it requires authentication. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior beyond the basic purpose.

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

Conciseness5/5

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

The description is a single, efficient sentence: 'Get explanations of Hacker News terms, culture, and conventions.' It is front-loaded with the core purpose, has no unnecessary words, and every part earns its place by specifying the action and scope. This makes it highly concise and well-structured for quick understanding.

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

Completeness3/5

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

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, output expectations, or integration with sibling tools. Without an output schema, it should ideally hint at what the explanations look like, but it doesn't, leaving some context incomplete for effective agent use.

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?

The input schema has 100% description coverage, with the 'term' parameter well-documented as 'HN term or concept (e.g., "karma", "flagged", "dupe", "Show HN", "Ask HN")'. The description adds no additional parameter semantics beyond what the schema provides, such as examples or usage tips. Since schema coverage is high, the baseline score of 3 is appropriate, as the schema adequately handles parameter documentation.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Get explanations of Hacker News terms, culture, and conventions.' It specifies the action ('Get explanations') and the resource ('Hacker News terms, culture, and conventions'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'user_analysis' or 'search_hn', which might also provide explanatory information in different contexts.

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 by mentioning 'terms, culture, and conventions,' suggesting it's for understanding Hacker News-specific concepts. However, it lacks explicit guidance on when to use this tool versus alternatives like 'search_hn' for general searches or 'user_analysis' for user-related insights. No exclusions or clear alternatives are provided, leaving some ambiguity in context.

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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