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slack_session_report

Read-onlyIdempotent

Report counts only for Slack messages read, outside-authored messages by origin, send attempts, and held sends to verify what reached the model and what tried to send.

Instructions

What this server process has actually done, as counts: how many messages it read, how many of those were written by authors outside this workspace broken down by origin, how many sends were attempted, and how many were held. A provenance label is a claim about one message; this is the claim about the whole session, and it is the only way to check after the fact whether outside-authored text reached the model and whether anything tried to send on the back of it. Counts only — no message text, no channel name, no user id is recorded. The receipt and the strict hold belong to this server process, so over HTTP every client of the process shares them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv5.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/no-open-world, but the description adds real behavioral context beyond them: counts only, no message text, channel name, or user id recorded, and the receipt/hold state is process-scoped and therefore shared across all HTTP clients. These are privacy and scope facts an agent cannot get from the annotations.

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

Conciseness3/5

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

Front-loaded with the core ('What this server process has actually done, as counts'), but the middle 'provenance label is a claim about one message; this is the claim about the whole session' is conceptual elaboration that lengthens the paragraph without adding call-time information.

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?

With no output schema and no parameters, the description must explain what comes back, and it does enumerate the count categories plus the privacy limits. Adequate for a single-argless audit tool, though actual field names/shape remain unspecified.

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

Parameters4/5

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

Zero parameters, so per the rubric the baseline is 4. The description correctly implies a no-argument call and adds no misleading parameter claims.

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?

States a specific resource and scope ('what this server process has actually done, as counts') and enumerates the exact counts returned (messages read, outside-authored by origin, sends attempted, sends held). It is clearly the session-audit tool among the siblings, though it never names a sibling it differs from.

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?

It gives a clear when-to-use: 'the only way to check after the fact whether outside-authored text reached the model and whether anything tried to send on the back of it.' No explicit exclusions or named alternatives, so it stops short of a 5.

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