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 of behavioral disclosure. It mentions that the tool 'decomposes the query into multiple perspectives and merges results' and that 'Each result includes a confidence verdict,' which adds some behavioral context. However, it lacks details on permissions, rate limits, error handling, or what 'confidence verdict' entails, leaving gaps for a tool with 5 parameters and an output schema.

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 concise and front-loaded, with the core purpose stated first. All sentences are relevant, explaining the method and usage. However, it could be slightly more structured by separating usage guidelines into a distinct part, but it's efficient with zero waste.

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 (5 parameters, no annotations, but with an output schema), the description is somewhat complete. It explains the purpose and method but lacks details on parameters, behavioral traits, and how the output schema relates. The output schema reduces the need to explain return values, but more context on usage and limitations would improve 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%, so the description must compensate. It doesn't mention any parameters explicitly, such as 'query,' 'top_k,' or date filters. While it implies query usage through 'Search memories,' it adds no semantic details beyond what the schema titles provide. With 5 parameters and no schema descriptions, this is a minimal baseline score.

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: 'Search memories using multiple query angles for better recall.' It specifies the verb ('search'), resource ('memories'), and method ('multiple query angles'). However, it doesn't explicitly distinguish it from sibling tools like 'recall' or 'deep_search' beyond mentioning 'Like deep_search but for memories,' which is somewhat helpful but not fully differentiating.

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 clear usage context: 'Use when recall misses relevant memories.' This indicates when to prefer this tool over alternatives like 'recall.' It also mentions 'Like deep_search but for memories,' hinting at a comparison. However, it doesn't explicitly state when not to use it or list all relevant alternatives, such as 'list_memories' or 'search_by_category.'

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