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slack_react

Add an emoji reaction to a Slack message using the channel, timestamp, and emoji name. The reaction is applied to the message as the user.

Instructions

Add a reaction (emoji) to a Slack message. The reaction appears as if you added it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelYesChannel containing the message (#name, @user, or ID).
reactionYesEmoji name without colons (e.g. 'thumbsup', 'eyes', 'white_check_mark').
timestampYesTimestamp (ts) of the message to react to.
workspaceNoWorkspace alias. Omit to use default.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.0.5

TDQS

A4/5.0
Behavior3/5

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

With no annotations present, the description carries the behavioral disclosure burden. 'The reaction appears as if you added it' provides useful identity/actor context beyond the schema. However, it does not mention potential side effects, failure conditions, or whether reactions are idempotent, so some transparency gaps remain.

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?

Two short, direct sentences with no filler. The core action is front-loaded, and the extra sentence about appearance adds meaningful behavioral context rather than redundant detail.

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

Completeness4/5

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

For a simple mutation tool with all parameters documented in the schema and no nested structures or enums, the description is mostly sufficient. The only minor gap is not describing the expected return value or error behavior, since there is no output schema to convey that.

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 all four parameters are already documented in the schema. The description adds no additional parameter-level meaning beyond what the schema provides, which matches the baseline for high schema coverage.

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 states a specific verb ('Add'), a specific resource ('reaction to a Slack message'), and the emoji context. Among the sibling slack_* tools, this is the only reaction-focused tool, so it is clearly distinguishable without opening the schema.

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 clearly implies when to use this tool: whenever an emoji reaction needs to be added to a Slack message. It does not explicitly discuss exclusions or alternatives, so it falls just short of the top score, but the intended usage context is unmistakable.

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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