user_analysis

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. While it mentions what gets analyzed (profile, karma, submissions), it doesn't describe key behavioral traits such as whether this is a read-only operation, what the output format looks like, potential rate limits, or authentication needs. For a tool with no annotation coverage, this is a significant gap in transparency.

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 without unnecessary words. Every part of the sentence ('Analyze a Hacker News user's profile, karma, and recent submissions') directly contributes to understanding the tool's function, making it appropriately concise and well-structured.

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 (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects like output format or operational constraints. Without annotations or an output schema, the description should do more to compensate, but it only meets the minimum viable threshold.

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%, so the schema already fully documents both parameters (username and submissionLimit). The description doesn't add any parameter-specific semantics beyond what's in the schema, such as explaining how submissionLimit affects the analysis or providing examples beyond the schema's descriptions. 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 tool's purpose: 'Analyze a Hacker News user's profile, karma, and recent submissions.' It specifies the verb ('analyze'), resource ('Hacker News user'), and scope ('profile, karma, and recent submissions'). However, it doesn't explicitly differentiate from sibling tools like 'hn_explain' or 'search_hn' which might also involve user-related analysis, so it falls short of a perfect score.

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 context by specifying what it analyzes (user data), but doesn't provide explicit guidance on when to use this tool versus alternatives like 'search_hn' for broader searches or 'hn_explain' for explanations. It lacks clear when/when-not statements or named alternatives, leaving usage somewhat ambiguous.

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