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

Beyond annotations (read-only, idempotent), the description discloses key behavioral traits: uses vector embeddings, returns similarityScore and matchExplanation, and notes that it is a paid feature counting toward monthly searches. This provides useful context about how the tool behaves and its limitations.

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 front-loaded with the primary purpose. Each sentence adds value: purpose, output details, use case, technology, and constraints. Slight redundancy between 'semantic similarity' and 'vector embeddings' but not excessive.

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?

With no output schema, the description does a good job explaining return values (similarityScore, matchExplanation). It covers the conceptual basis (semantic similarity) and operational constraints (paid, monthly count). Minor gaps include error behavior or handling of no similar results, but overall adequate for an agent to select and invoke correctly.

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 parameters are well-documented in the schema. The description does not add much parameter-specific meaning but does clarify the output semantics (similarityScore, matchExplanation), which helps understand what the parameters affect. Baseline 3 is appropriate given high schema coverage.

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: finding opportunities similar to a given one using semantic similarity, and distinguishes it from keyword-based search tools. The verb 'Find' plus the resource 'opportunities similar to a given one' is specific and differentiates from sibling search tools.

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?

Explicitly states when to use: 'Useful when user likes one result and wants more like it.' It also contrasts with keyword matches, implying the alternative of search tools. Does not explicitly name alternatives or exclusions, but provides clear usage context and constraints (paid feature, monthly searches).

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