get_sector_briefing

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

Beyond annotations indicating read-only behavior, the description adds key behavioral details: exclusion of net-loss stocks for PER/ROE and negative-book for PBR, margin_ratio nullability condition, and cache-only execution.

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, front-loaded with purpose, and well-structured with usage, behavioral notes, and parameter details without superfluous 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?

Given the presence of output schema and annotations, the description covers all necessary aspects: purpose, usage guidance, behavioral nuances, and parameter specifics, leaving no gaps.

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?

With 0% schema description coverage, the description fully explains the lone parameter (sector_type with allowed values and default), adding meaning beyond the schema's type/default.

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 returns sector-level median financial ratios (PER, PBR, ROE, margin ratio) and distinguishes from siblings like get_market_briefing (market-wide) and get_stock_briefing (single stock).

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?

It provides explicit use cases (e.g., sector valuation queries) and references alternative tools, giving good context for when to use this tool, though without explicit when-not-to-use statements.

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