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

Adds substantial context beyond the readOnlyHint/openWorldHint annotations: coverage is sparse, no automated KPI feed exists, and results carry stored fiscal periods, units and source links. The trailing 'Read-only' merely repeats the annotation, and nothing is said about ordering or empty-result behavior, so it stops short of a 5.

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?

Four short sentences, front-loaded with the operation, then the sparse-coverage caveat, then the prerequisite, then return shape. Only the redundant 'Read-only' tail fails to earn its place.

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?

With no output schema, the description does the work of describing returns (fiscal periods, units, source links) and sets expectations about sparse coverage and the separate company-economics dataset. Complete enough to call correctly; only minor gaps like empty-result handling remain.

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 ticker format, category, metricKey and limit are already fully documented in the schema. The description reinforces the ticker exactness requirement but adds no new syntax or constraint information beyond that; baseline 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 verb and resource ('Read curated, source-linked operating KPI observations') scoped to 'one exact Bullrun ticker', and explicitly separates itself from the 'company-economics observations' dataset. An agent can distinguish it from siblings like get_revenue_breakdown or get_financial_history without opening a 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 routes the agent: 'Check get_company_data_coverage first', plus a clear when-NOT clause ('do not assume ARR, retention, customer counts or payments metrics are available'). It names both the prerequisite tool and the excluded dataset, leaving little inference.

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