vector_store_add

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

With no annotations, the description fully carries the burden and excels. It discloses the provider selection order (Voyage → OpenAI → Gemini → local hash), override mechanisms, env var config, optional doc_id UUID generation, and the metadata_json format. This goes well beyond the bare schema and gives the agent critical operational knowledge.

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 well-structured and appropriately sized. The opening sentence states the purpose, the provider order is a necessary complexity, and the Args list is compact and scannable. Every sentence contributes value without bloat.

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 tool with 7 parameters, no annotations, and no schema descriptions, the description is remarkably complete. It covers the embedding pipeline, all parameters, provider override logic, and configuration via env vars. With an output schema present, the lack of return value detail is acceptable. The only minor omission is behavior for unknown collections, but this does not undermine overall 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?

Schema description coverage is 0%, but the description thoroughly explains every parameter in the Args section: collection's logical name, text's full text to embed, doc_id's optional stable id, metadata_json's form, and provider/model/dimensions as overrides. This adds substantial meaning beyond the schema's bare types and defaults.

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 function: 'Embed and store text in a named collection for later similarity search.' The verb 'embed and store' plus resource 'named collection' is specific and distinguishes it from sibling tools like vector_store_search and vector_store_list.

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 gives strong context for when to use this tool (when adding text to a vector store for later retrieval) and implicitly contrasts with search/list siblings. However, it does not explicitly state alternatives or when-not-to-use, such as 'use vector_store_search to query.'

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