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

Even though annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds substantial behavioral context: daily generation, public-source-only data, Critical briefs limited to verifiably ≤7-day-old facts, N2/Apple omission, and the distinction between machine-feed and published briefs. No contradiction with annotations exists.

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 lengthy but well-structured with clear sections and front-loaded operational facts. Some promotional phrasing such as 'No pure-news source does this' and 'UNIQUELY' adds little functional value, but most sentences contribute useful detail or navigation guidance.

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?

For a tool with no output schema and five optional parameters, the description is remarkably complete: it documents return fields, filter semantics, provenance, output quality signals, public-versus-machine-feed behavior, citation instruction, and sibling-tool boundaries. An agent has enough information to select and invoke the tool 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 0%, so the description carries the full burden and does so thoroughly. It explains severity values, category values, since as an ISO timestamp, publishedOnly as a boolean, and limit with range and default. This compensates fully for the empty parameter descriptions in the input schema.

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 defines the tool as returning sourced semiconductor market briefs and enumerates the exact output fields and categories. It also differentiates the tool from sibling tools through explicit DO NOT USE guidance naming get_accelerator_costs, get_wafer_pricing, calculate_chip_cost, get_recent_changes, and get_foundry_allocation.

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 explicit USE THIS FOR scenarios with concrete example queries, and DO NOT USE alternatives with the exact sibling tools to route to instead. This gives an agent unambiguous decision criteria for when this tool is appropriate versus alternatives.

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