Slack MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: the tool performs a search operation (implying read-only, non-destructive behavior), requires a specific token type (User Token), and supports Slack search modifiers. However, it lacks details on rate limits, error handling, or pagination, which are common for search tools.

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 appropriately sized and front-loaded, starting with the core purpose, followed by important notes and parameter details in a structured format. Every sentence adds value, with no redundant or wasted information, making it easy for an AI agent to parse and understand quickly.

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 (search across multiple resource types), no annotations, and an output schema present (which handles return values), the description is complete enough. It covers purpose, usage guidelines, token requirements, and parameter semantics, providing all necessary context for an AI agent to select and invoke the tool correctly without over-explaining.

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 0%, so the description must compensate. It adds significant meaning beyond the schema by explaining each parameter's purpose, default values, and constraints (e.g., 'count: Number of results per type (1-100)'). The only gap is that 'sort' and 'sort_dir' enums are implied but not explicitly listed as such, slightly reducing clarity.

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 searches both messages and files across the Slack workspace, using specific verbs ('Search') and resources ('messages and files'). It distinguishes itself from sibling tools like 'search_files' and 'search_messages' by explicitly covering both types of content in a single operation.

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 provides explicit guidance on when to use this tool versus alternatives by noting it searches 'both messages and files,' implying that for single-type searches, the sibling tools 'search_files' or 'search_messages' should be used. It also specifies the required token type (User Token vs. bot tokens), which is crucial for correct invocation.

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