Project Tessera

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

No annotations are provided, so the description carries the full burden. It mentions that 'memories will be automatically categorized and stored in Tessera', which adds some behavioral context about the outcome. However, it lacks details on permissions, error handling, rate limits, or what happens if the data format is invalid, leaving significant gaps for a mutation tool.

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, well-structured sentence that efficiently conveys the action, parameters, and outcome without any wasted words. It is front-loaded with the core purpose and includes essential details concisely.

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 that there is an output schema (which reduces the need to describe return values) but no annotations and low schema coverage, the description is moderately complete. It covers the basic operation and parameters but lacks depth on behavioral aspects like error handling or side effects, which are important for an import tool.

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%, so the description must compensate. It adds meaning by explaining that 'data' should be 'exported JSON data' and 'source' specifies the AI tool, which clarifies the parameters beyond the schema. However, it doesn't detail the JSON structure, validation rules, or default behavior for 'source', leaving some ambiguity.

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 verb ('import') and resource ('memories') with the source ('from another AI tool'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'import_memories' or 'import_conversations', which might handle similar imports but from different sources or formats.

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 by specifying the source options ('chatgpt', 'gemini', or 'standard'), but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'import_memories' or 'import_conversations'. No exclusions or prerequisites are mentioned.

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