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iskifogl

Slack MCP Server

by iskifogl

slack_search_messages

Search for messages across all Slack channels using query syntax like from:user, in:channel, or has:reaction to find specific conversations.

Instructions

Search for messages across all channels (requires user token with search:read scope)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query (supports Slack search syntax: from:user, in:channel, has:reaction, etc.)
countNoNumber of results per page (max 100)
pageNoPage number
sort_byNoSort results by relevance score or timestamptimestamp
sort_dirNoSort directiondesc
Behavior3/5

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 adds valuable context about authentication requirements ('requires user token with search:read scope'), which isn't covered elsewhere. However, it doesn't describe other behavioral traits like rate limits, pagination behavior beyond parameters, or what the search results look like (format, fields returned). This leaves gaps for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose and includes essential context (authentication requirement). Every word earns its place with zero waste or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (search across all channels with 5 parameters), no annotations, and no output schema, the description is incomplete. It covers authentication and purpose but lacks details on return values, error conditions, or behavioral constraints like rate limits. The high schema coverage helps, but for a search tool with no output schema, more context would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 5 parameters thoroughly (e.g., query syntax, count max, sort options). The description adds no additional parameter semantics beyond what's in the schema. According to the rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Search for messages') and scope ('across all channels'), distinguishing it from sibling tools like slack_get_messages (which retrieves messages from a specific channel) or slack_get_thread_replies (which focuses on thread replies). The verb+resource combination is precise and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('Search for messages across all channels') and provides a prerequisite ('requires user token with search:read scope'). However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the siblings (e.g., slack_get_messages for channel-specific retrieval), which prevents a perfect score.

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

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