add_text_to_index

Does 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 effectively describes key behaviors: it adds documents to the knowledge base, handles content chunking for documents over 1000 words, and updates both JSON storage and Elasticsearch index. This covers mutation effects, processing logic, and data persistence, though it could mention permissions or error handling.

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 appropriately sized and front-loaded, with the core purpose stated first, followed by behavioral details and parameter explanations. Every sentence adds value, though the 'Args' section could be integrated more smoothly. It avoids redundancy and is efficient for a tool with two parameters.

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 (mutation with data processing), no annotations, and an output schema present (which handles return values), the description is largely complete. It covers purpose, behavior, and parameters, but could improve by mentioning prerequisites or error cases. The output schema reduces the need to explain return values, making this adequate.

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 description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'title' is a descriptive title for the text and 'content' is the actual text content to index, providing clear context for both parameters. This compensates well for the lack of schema descriptions, though it doesn't detail constraints like length or format.

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 with a specific verb ('Adds') and resource ('new text document to the knowledge base'), distinguishing it from siblings like 'index_documents' (which might handle multiple documents or different formats) and 'ingest_pdfs' (which handles PDFs specifically). It specifies the exact action and target resource.

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 for adding text documents to the knowledge base, but does not explicitly state when to use this tool versus alternatives like 'index_documents' or 'ingest_pdfs'. It provides context (adding text documents) but lacks explicit guidance on exclusions or comparisons to sibling tools.

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