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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), and the description goes well beyond them: periodic-refresh staleness, credential-derived account ID, refusal of cross-account queries, and interpretation rules for LOW confidence / identity_only_rows / literal_only_result. That confidence-semantics guidance is genuinely non-obvious context. Minor deduction because the return-envelope listing duplicates what the output schema likely already declares.

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 core capability and the freshness caveat, then constraints, then return shape. Every sentence carries information, though terms like 'identity_only_rows' and 'literal_only_result' are dropped without definition and read as internal jargon.

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 single-parameter read tool with annotations and an output schema, this covers freshness, authorization scope, refusal behavior, and result-quality interpretation — the things an agent actually needs to act on results. The gap is routing guidance relative to the many overlapping account-analytics siblings.

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 coverage is 100% for the single 'question' parameter, so the schema carries the specification and baseline 3 applies. The description adds one real clarification — that the account ID is resolved from the credential and is not caller-supplied — which helps the agent understand why no account parameter exists, but says nothing about question formatting or scoping beyond 'natural-language'.

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 names a specific verb and resource ('Read a periodically refreshed summary of the authenticated account's firmographics and recent campaign history') and explicitly demarcates it from a live platform-state query. It does not name the closest sibling (query_metadata_analytics_benchmarks) or other account-stats tools, so an agent must still infer the boundary from the data source rather than from an explicit contrast.

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 gives one useful usage constraint — this is a warehouse snapshot, not live state — and states that cross-account queries are refused. However it never says when to prefer it over account_level_stats, account_funnel_reports, get_account_summary_insights, or query_metadata_analytics_benchmarks, all of which plausibly overlap, so tool selection is left to inference.

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