search_add_to_vector_db

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

With no annotations provided, the description carries the full burden. It discloses the write/non-destructive-add nature and the indexing mechanism, but does not mention error cases (e.g., whether adding a title that already exists overwrites or fails), rate limits, size constraints on content, or what the output/confirmation looks like despite having an output schema.

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?

Two concise sentences state the action and purpose without waste. The description is front-loaded with the main verb and resource, and the second sentence adds meaningful mechanistic context about embedding generation.

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?

For a fairly complex 9-parameter write tool with an output schema and 100% parameter coverage, the description covers the core purpose well. Given the output schema exists and the schema documents all params, the main gap is the absence of behavioral caveats (e.g., how duplicate titles are handled, whether content size is limited), but overall it is reasonably complete.

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 coverage is 100%, so every one of the 9 parameters has schema-level documentation. The description itself adds no parameter-specific detail beyond what the schema provides, which keeps it at the baseline 3 for full coverage. It doesn't clarify relationships between parameters (e.g., whether short_summary is auto-generated or required for better search).

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 uses specific verb+resource ('Add a new document to the project vector database') and clearly explains the mechanism: generates embedding and stores in Azure AI Search. It also distinguishes from the sibling tool 'search_vector_db' by positioning this as the write counterpart (add/produce vs search/query).

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 states what happens (embeds content and stores for future semantic searches) which implies it is used to populate the index before searching. However, it does not explicitly contrast with the sibling search_vector_db tool or mention when NOT to use this tool, nor any prerequisites like needing an index to exist first.

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