list_item_likes
Retrieve a list of users who liked a specific Qiita article to analyze engagement and community interaction.
Instructions
List likes on an item
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes | Item ID |
Retrieve a list of users who liked a specific Qiita article to analyze engagement and community interaction.
List likes on an item
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes | Item ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states what the tool does ('List likes on an item') without revealing any behavioral traits like pagination behavior, rate limits, authentication requirements, error conditions, or what format the output takes. For a list operation with zero annotation coverage, this is insufficient.
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 extremely concise ('List likes on an item') - just four words that directly convey the core functionality without any wasted words. It's front-loaded with the essential information and has no unnecessary elaboration.
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 that there are no annotations and no output schema, the description is incomplete for proper tool usage. While the purpose is clear, the description lacks crucial context about behavioral characteristics (like pagination, authentication needs, or rate limits) and doesn't explain what the output contains. For a list operation that likely returns structured data, this leaves significant gaps.
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%, with the single parameter 'item_id' clearly documented in the schema as 'Item ID'. The description doesn't add any meaningful parameter semantics beyond what the schema already provides, such as explaining what constitutes a valid item ID or providing examples. The baseline score of 3 reflects adequate but minimal value addition.
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 'List likes on an item' clearly states the verb ('List') and resource ('likes on an item'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling list tools like 'list_item_comments' or 'list_item_reactions', which have similar list-item-related patterns but different resources.
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 provides no guidance on when to use this tool versus alternatives. There are multiple sibling list tools (e.g., 'list_item_comments', 'list_item_reactions', 'list_item_stockers') that might be relevant for similar contexts, but the description doesn't indicate when this specific tool is appropriate or what distinguishes it from those other listing operations.
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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