Slack Max API MCP

ops_channel_snapshot

Capture channel activity data including volume, participants, threads, and reactions to analyze operational metrics and engagement patterns in Slack.

Instructions

Operational snapshot for a channel: activity volume, participants, threads, reactions, and recent samples.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "channel": "<channel>"
    },
    "name": "ops_channel_snapshot"
  }
}

Input Schema

Name	Required	Description	Default
`channel`	Yes
`lookback_hours`	No
`limit`	No
`participant_limit`	No
`sample_size`	No
`token_override`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.13Mar 30, 2026

TDQS

C2.6/5.0

Behavior2/5

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 lists returned data components but fails to indicate whether this is a safe read-only operation, if it generates audit logs, rate limits, or whether 'recent samples' implies sampling randomness or recency bias. Major safety and operational characteristics are missing.

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

Conciseness4/5

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

The description is a single, front-loaded sentence with no redundant phrases. Every word conveys meaningful content about the tool's output. However, given the complexity (6 undocumented parameters), extreme brevity becomes a liability rather than a virtue.

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

Completeness2/5

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

For a tool with 6 parameters (0% schema coverage), no output schema, and no annotations, the description is insufficient. It lists output categories but provides no parameter guidance, return format, pagination info, or error conditions. The gap between description content and required context is substantial.

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

Parameters1/5

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

Schema description coverage is 0% and the description mentions none of the 6 parameters. Critical relationships between parameters are unexplained: how 'limit' interacts with 'sample_size', what 'token_override' is for, or how 'participant_limit' differs from the participant count in the snapshot. The description completely fails to compensate for the schema's lack of documentation.

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

Purpose4/5

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

The description clearly states the tool provides an 'operational snapshot' and enumerates specific data components (activity volume, participants, threads, reactions, samples). However, it doesn't explicitly differentiate from sibling tools like 'ops_state_overview' or clarify that this is an analytics/inspection tool versus the action-oriented siblings (approve, revoke, broadcast).

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

Usage Guidelines2/5

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

No guidance provided on when to use this versus alternatives like 'ops_state_overview' or 'ops_recent_failures'. No mention of prerequisites (e.g., channel permissions) or when not to use it. The description only states what data is returned, not the decision criteria for selection.

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