Generate embeddings for emails that lack them, enabling semantic search and similarity analysis.
Generate embeddings for all emails that don't have them yet
| Name | Required | Description | Default |
|---|---|---|---|
| batch_size | No | Number of emails to process in each batch (default: 100) |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only implies idempotent behavior by saying 'don't have them yet', but doesn't disclose whether the operation is synchronous or asynchronous, whether it's safe to re-run, what happens to existing embeddings, or potential performance costs. For a state-changing batch operation, this is a significant gap.
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 with the core action front-loaded. It wastes no words, though it is arguably under-specified rather than optimally concise.
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 batch operation with no output schema and no annotations, the description lacks operational context: it doesn't mention error handling, progress reporting, whether it's a long-running job, or what the tool returns upon completion. An agent would have little idea what to expect when invoking it.
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 the batch_size parameter is fully documented in the schema. The description adds no parameter-specific information beyond what the schema provides, so the baseline 3 applies. The description doesn't clarify the practical effect of adjusting batch_size.
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 states a specific verb ('Generate') and resource ('embeddings for all emails that don't have them yet'), which clearly differentiates it from sibling tools like send_email or search_emails. The qualifier 'that don't have them yet' adds useful specificity about the target population, though it doesn't explicitly explain what embeddings enable (e.g., semantic search).
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?
No guidance is given on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., emails must exist first) or whether it should be run before semantic_search_emails to populate the index. There are no explicit when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.