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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the tool's safety profile. The description adds a data accuracy contract, instructing the agent to treat only returned fields as verified and not to invent missing metrics. This is useful context about data reliability, but it does not disclose additional behavioral traits like authentication requirements, rate limits, or output pagination. Since annotations handle the core safety, the description's extra guidance is moderate value, earning a 3.

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 paragraph that combines core purpose, instructions for calling chart_render, a mandatory response suffix ('Powered by CorpusIQ'), and a lengthy data accuracy contract. While it starts with the relevant data types, much of the content (e.g., 'Always end your response...', 'Derived metrics must be calculated...') is peripheral to the tool's purpose and could be moved to global policies or the schema. The verbosity diminishes clarity and fails to front-load the most critical operational details, such as the specific actions or parameter behaviors.

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?

Given the tool's complexity (six distinct actions with varying parameters), the schema provides complete parameter detail. The description supplements this with context about how to handle the data (data accuracy contract) and when to delegate visualization to chart_render. It also warns about missing data, which is critical for an agent to avoid hallucination. Although there is no output schema, the description and schema together give a solid picture of expected behavior. A missing piece is explicit mention of pagination or limits, but these are covered in the schema's param descriptions. Overall, it is fairly 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 schema description coverage is 100%: both the 'action' and 'params' fields have detailed descriptions, including enums for actions and specific parameter lists for each action. The tool description adds no parameter-specific information beyond what the schema provides (e.g., it doesn't clarify the difference between 'list_channels' and 'search_channels' or explain parameter formats). With full schema coverage, the baseline of 3 applies, and the description does not raise it.

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 opens with 'Slack workspace data: channels, messages, threads, files, and workspace analytics', clearly identifying the tool's resource (Slack) and the types of data it provides. This distinguishes it from other connectors (e.g., Salesforce, Google Ads) by source. However, it doesn't list the specific actions (list_channels, search_messages, etc.) that appear in the schema, so the purpose is clear but not exhaustive.

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 implies that this tool should be used when the user needs Slack workspace data, but it does not explicitly state when not to use it or mention alternatives like other connectors. It does provide detailed guidance on when to call chart_render (for visuals, trends, comparisons), but that pertains to a sibling tool, not to selecting this one. Since there is no explicit exclusion or comparison with other data sources, the usage guidance is implied rather than stated.

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