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

With no annotations provided, the description carries the behavioral disclosure burden. It reveals the output shape and the dominant perspective enum, which is useful. However, it does not disclose edge-case behavior, how inputs influence the score, whether state changes, or what happens with incomplete category data, leaving notable behavioral gaps.

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 dense sentence that front-loads the primary output and includes the key output variants. Every phrase adds information, with no filler or redundant restatement of the tool name.

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?

The tool has four parameters including a nested object, no output schema, and no annotations, so the description must carry substantial context. It names the outputs but omits parameter semantics, calculation logic, defaults behavior, and how categoryCounts relates to the dominant perspective. This is insufficient for reliable invocation.

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 0%, so the description must compensate for parameter meaning, but it does not explain painMentions, categoryCounts, intentMentions, or urgencyMentions. It only mentions 'total mentions' and 'dominant perspective' at a high level, which does not tell the agent how to populate or interpret the parameters.

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 computes social_pain_score with an explicit range (0-30), total mentions, and a dominant perspective with enumerated options. It is unambiguous and distinct from sibling tools by resource and output, though it does not explicitly contrast itself with any sibling.

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?

There is no guidance on when to use this tool versus any alternative. It does not mention intended use cases, prerequisites, or suggest when another compute_* sibling might be more appropriate. The only inferred usage is from the function name, which is not explicit guidance.

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