add_web_search_evidence

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

With no annotations provided, the description carries the full burden of explaining behavior. It describes that extracted fields are 'stored as evidence' and optionally 'merged into the professor's profile with cross-source verification.' It also mentions the return format. However, it does not detail failure modes, permissions required, or the exact nature of 'cross-source verification.' Still, it provides sufficient transparency for an additive operation.

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 concise: one purpose sentence, one usage guideline sentence, a bulleted Args list, and a return description. Every sentence adds value. The Args list is well-organized but not overly verbose. No redundant information. It is efficiently structured and easy to scan.

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 complexity (8 parameters, nested object, no output schema), the description covers inputs and output comprehensively. It explains the return dict keys (evidence_id, merged, verification_status). However, it lacks explanation of error cases, rate limits, or potential side effects (e.g., whether merging is reversible). For a tool that modifies professor profiles, this omission slightly reduces completeness.

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?

The schema description coverage is 0%, so the description must compensate fully. It does so by listing each parameter with its purpose and allowed values: e.g., 'source_type: One of: faculty_page, personal_homepage...', and for extracted, 'Supported keys: homepage_url, name, institution...' It also specifies defaults for optional parameters like confidence and auto_merge. This adds substantial meaning beyond the raw schema.

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 primary action: 'Add WebSearch evidence for a professor and optionally merge it into their profile.' It provides a specific verb ('Add') and resource ('WebSearch evidence'), and distinguishes from sibling tools like 'update_professor_profile' which update profiles without an evidence step. The purpose is unambiguous and immediately understandable.

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 explicitly states when to use the tool: 'Call this after using web search to find a professor's faculty page or personal homepage.' This provides clear context for invocation. However, it does not explicitly mention when not to use it or list alternative tools for similar tasks, though no sibling tool performs the same evidence-adding function. The guidance is useful but could be more comprehensive.

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