get_earnings_intelligence

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

Annotations already disclose readOnlyHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond them: provenance tags ('knowledge_graph' or 'web_supplemental'), the confirmed_absent brands behavior on multi-company queries, and server-side intent routing to avoid conflation—all useful and non-obvious.

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?

Information-dense and largely front-loaded, with the primary purpose first and routing/examples after. It is long, but nearly every sentence carries distinct routing or semantic value, so little is wasted.

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?

Although there is no output schema, the description explains what results contain (active initiatives plus confirmed_absent brands, provenance tags), which is exactly what an agent needs to interpret a call. Nothing essential is missing for a 10-parameter, zero-required read tool.

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 100% schema coverage the baseline is 3, but the description adds genuine meaning: it explains the activity enum's 'sustainability' semantics and warns about conflation with analyst margin-sustainability questions, and it gives search-term examples ('labor costs', 'tariff guidance'). This goes beyond the schema text.

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 verb+resource ('cross-company thematic earnings intelligence from the knowledge graph and web sources') and immediately differentiates itself from siblings by naming the use cases it owns vs. those that belong to get_company_earnings and brand_tracker. An agent can route without reading 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?

Explicitly enumerates when to use it (multi-company comparisons, industry-level, sector filters, activity categories) and names two alternatives with the conditions that select them: 'For single-brand earnings, brand_tracker…' and 'For per-ticker structured analysis… use get_company_earnings.' This is near-ideal routing guidance.

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