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 discloses key behavioral traits: the tool decomposes queries into 2-4 perspectives (core keywords, individual terms, reversed emphasis), merges results, and includes verdicts (confident match, possible match, low relevance). This covers the search process and output format, though it lacks details on performance or limitations like rate limits.

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 front-loaded with the core purpose, followed by operational details and usage guidelines in three concise sentences. Every sentence adds value: the first defines the tool, the second explains its method and output, and the third specifies when to use it, with zero wasted words.

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 (multi-angle search) and no annotations, the description does well by explaining the process and output verdicts. With an output schema present, it doesn't need to detail return values. It covers the 'what' and 'when' effectively, though it could add more on behavioral constraints like error handling or performance.

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 schema provides no parameter details. The description adds no explicit parameter semantics—it doesn't explain 'query', 'top_k', 'project', or 'doc_type'. However, the context of search is implied, and with an output schema present, some burden is reduced. Baseline 3 is appropriate as the description doesn't compensate for the coverage gap but doesn't mislead.

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 documents using multiple query angles for better recall.' It specifies the verb ('search'), resource ('documents'), and distinct approach ('multiple query angles'), differentiating it from sibling tools like 'search_documents' or 'unified_search' by emphasizing decomposition into perspectives and merging results.

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 explicitly provides usage guidance: 'Use when standard search misses relevant results.' This directly tells the agent when to choose this tool over alternatives, such as 'search_documents' (implied as 'standard search'), making it clear for decision-making.

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