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

The description discloses that the tool does not fetch or verify data, labels results as unverified, and enforces a data accuracy contract with specific prohibitions. It also mentions the required 'Powered by CorpusIQ' suffix. This goes beyond the annotations' read-only and idempotent hints, adding significant transparency about data handling and output constraints.

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 dense but each sentence contributes substantive information (usage, data provenance, accuracy rules, output formatting). It avoids fluff and is appropriately sized for the complexity of behaviors it explains.

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 description covers the tool's purpose, usage context, data limitations, accuracy contract, required output text, and relationship to sibling tools. It mentions the output format (PNG + text summary) and even the required closing phrase. The presence of an output schema supplements the return behavior, making the description highly 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?

The description does not elaborate on most parameters beyond what the schema provides. It does clarify the 'source' field as a display label only, but the schema already includes that. The description's focus on derived metrics indirectly clarifies the 'data' parameter but does not systematically explain each field. With low schema description coverage, the description adds limited parameter-level guidance.

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 clearly states the tool's function: rendering numeric data as a deterministic PNG and text summary. It distinguishes itself from dashboard_render by specifying it handles model-provided data, making the purpose unambiguous.

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 states when to use the tool ('when the user asks to visualize, chart, recap, or compare values already present in the conversation') and when to use an alternative ('For verified live GA4 data use dashboard_render instead'). Provides clear direction for selection.

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