get_company_earnings

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

Annotations already declare readOnly/idempotent/openWorld and non-destructive, so the safety profile is covered. The description adds genuine behavioral context: coverage is limited to 517 consumer-sector tickers and uncovered tickers fall back to web-backfill, which warns the agent that result provenance and completeness vary. It stops short of rate-limit or latency details, but for a read tool this is solid.

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?

Front-loaded with the identity of the tool, then contents, coverage/fallback, and routing guidance in a tight sequence. Every sentence carries signal, though the parenthetical list and Fodda provenance reference make it slightly dense.

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?

No output schema exists, so the description usefully summarizes what the record returns and its coverage/fallback behavior, which is the critical context. For a nine-parameter tool the individual modes are left to the schema, which fully covers them, keeping this near-complete.

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 all nine parameters (including the mode/view enums and required-for relations) are already documented in the schema. The description adds no parameter-level guidance, so the baseline of 3 applies.

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?

States a specific resource (per-ticker earnings) with clear scope ('canonical per-ticker earnings source') and enumerates what the record contains (analyst concerns, sentiment, activity, CEO intelligence, validated trends). It explicitly differentiates itself from the sibling get_earnings_intelligence, so an agent can route without opening either schema.

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?

'Use this for company-specific data. Use get_earnings_intelligence for cross-company thematic comparisons' gives explicit when-to-use and names the alternative with the discriminating condition. Nothing is left to inference for selection.

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