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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by disclosing the output composition — grouping by reasons/factors with attribution, ranking, and supporting-deal evidence — which orients the agent to the result shape. The word 'Return' is consistent with the read-only annotation; no contradiction exists.

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 a single dense sentence with no wasted words. The primary action and output structure are front-loaded. It could arguably be split for readability, but it is appropriately sized and efficient.

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?

The tool is complex (13 parameters, several exclusive selectors, multiple enum-driven options), yet the description is just one sentence. The output schema covers return values, but the description does not address usage context, selector exclusivity, or how this analysis differs from the adjacent get_deals tool. For a tool this complex, additional guidance would be warranted.

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 54%, which sits between the high and low thresholds, so the description carries a moderate burden. It indirectly maps to signal_rank_by (ranking), signal_attribution_mode (attribution), and include_supporting_deals (supporting-deal evidence), which adds some value. However, it doesn't clarify the required deal_statuses or the semantics of the exclusive selector filters (team_ids, owner_ids, owner_scope) that would matter for correct invocation.

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 states a specific verb ('Return'), a clear resource ('Data Parrot closed-deal analysis'), and enumerates the output groupings (win/loss reasons, sales performance factors, buyer decision factors) plus attribution, ranking, and evidence. This is a specific and informative purpose statement. However, it doesn't explicitly differentiate from siblings like get_deals, which could also surface closed-deal data, so it loses the full point.

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?

The description gives no guidance on when to use this tool versus the 13 sibling tools, including close relatives like get_deals, get_forecast, and get_pipeline_history. No exclusions, prerequisites, or alternative tool references are provided. The agent must infer the analytical use-case context entirely on its own.

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