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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds substantial behavioral context beyond annotations: the discoverability filter, ranking by trust tier and verified completions, the AI-inferred skill provenance, and the explicit privacy guarantee ('never phone, email, or org membership'). This is high-value transparency about what the tool does and does not return.

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?

Three sentences, each earning its place: the first defines purpose and ranking, the second explains skill provenance, and the third specifies privacy-safe output fields. Key info is front-loaded, and there is no filler or repetition of schema content.

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?

Despite lacking an output schema, the description covers the essential return contract: sanitized public cards with specific fields and exclusions. It also covers the selection logic, ranking, and all filters. An agent has enough context to call this tool correctly and interpret results without further inference.

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?

Input schema coverage is 100%, so the schema already documents all five parameters well. The description does not add per-parameter detail beyond the schema, but it does provide useful context for how the parameters shape results (e.g., ranking and sanitized output). Baseline 3 is appropriate because the schema carries the parameter documentation burden.

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 states a specific verb ('Search'), a specific resource ('cross-org Worker Marketplace'), and precisely defines the population ('workers who opted in (discoverable=true on their passport)'). It also gives unique ranking criteria ('passkey trust tier + verified completion volume'), which distinguishes it clearly from sibling list/search tools like tascan_list_workers or tascan_find.

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 clearly establishes when this tool is appropriate: searching the cross-org marketplace for opt-in workers. It provides filter guidance through examples and constraints, but it does not explicitly name sibling alternatives or state when not to use it, so there is a small exclusion-guidance gap.

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