add_context

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 states the tool adds context to a vector database for later retrieval, implying a write operation, but doesn't disclose critical traits: whether this is idempotent (e.g., overwrites existing IDs), requires specific permissions, has rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 highly concise and well-structured in two sentences: the first states the purpose, and the second provides usage guidance. Every sentence earns its place without redundancy or fluff, making it easy to parse and front-loaded with essential information. It efficiently communicates core functionality within minimal text.

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 3 parameters, no output schema, and no annotations), the description is minimally adequate. It covers the basic purpose and usage but lacks details on behavioral traits, error handling, or output expectations. Without annotations or output schema, the description should do more to explain what happens after invocation (e.g., success confirmation, error cases). It meets a bare minimum but has clear gaps for a write operation.

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 100%, so the schema fully documents the three parameters (id, content, metadata) with their types and descriptions. The description adds no parameter-specific semantics beyond implying storage and indexing, which is already covered by the tool's purpose. Baseline 3 is appropriate as the schema does the heavy lifting, and the description doesn't compensate with additional insights like format examples or constraints.

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: 'Add a piece of context/knowledge to the vector database' with the specific action 'store information that can be retrieved later'. It distinguishes from siblings like delete_context (removal) and query_context (retrieval), though it doesn't explicitly differentiate from add_contexts_batch (batch version). The verb+resource combination is specific but could be more precise about the 'add' operation versus batch alternatives.

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 provides implied usage guidance: 'Use this to store information that can be retrieved later for relevant queries' suggests it's for storing data for future retrieval. However, it lacks explicit when-to-use vs. when-not-to-use criteria, doesn't mention alternatives like add_contexts_batch for multiple entries, and omits prerequisites or constraints. The guidance is functional but incomplete for optimal tool selection.

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