search_hn

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return type ('matching content with relevance scores'), which is helpful, but fails to address critical aspects like rate limits, authentication needs, error handling, or pagination behavior. For a search tool with 5 parameters, this leaves significant gaps in understanding how the tool behaves in practice.

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 a single, efficient sentence that front-loads the core purpose ('Search Hacker News stories and comments') and immediately states the return value. Every word earns its place with zero redundancy or fluff, making it easy for an agent to parse quickly.

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 moderate complexity (5 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and return type but lacks behavioral details (e.g., rate limits, errors) and output structure clarification. Without an output schema, the agent must infer the exact format of 'matching content with relevance scores'.

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?

Schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain query syntax, tag combinations, or how relevance scores are calculated). Baseline 3 is appropriate when the schema does the heavy lifting.

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 specific action ('Search Hacker News stories and comments') and resource ('Hacker News'), distinguishing it from siblings like 'browse_stories' (likely browsing without search) and 'get_story_details' (fetching specific story details). It explicitly mentions what it returns ('matching content with relevance scores'), making the purpose unambiguous.

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 usage for search scenarios but provides no explicit guidance on when to use this tool versus alternatives like 'browse_stories' or 'hn_explain'. It lacks any 'when-not' or prerequisite information, leaving the agent to infer context from the tool name and description alone.

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