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brief-mcp

brief-mcp

by MLDreamer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Brief All Today

brief_all_today

Generates briefs for all of today's meetings by fetching the calendar and researching each attendee once, so you can prepare for the day in a single pass.

Instructions

Generate meeting briefs for ALL of today's meetings.

Fetches today's calendar, then researches all attendees across all meetings in parallel (deduplicated — each person only researched once even if they appear in multiple meetings). Perfect for morning prep.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "brief_all_today"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations present, the description carries the behavioral burden and does disclose meaningful execution semantics: it fetches today's calendar and researches attendees in parallel with deduplication, which signals cost/scope behavior an agent should anticipate. It does not say whether anything is persisted or what happens on a day with no meetings, leaving a modest gap.

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 sentences, front-loaded with the scope constraint, and the mechanism (parallel, deduplicated research) is compressed into a parenthetical rather than explicated. Nothing is wasted and nothing essential is buried.

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

Completeness5/5

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

The tool is zero-parameter and has an output schema, so return values need not be described. Scope, execution behavior, and intended use are all covered, leaving nothing an agent needs in order to invoke it correctly.

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?

The tool takes no parameters and the schema has 100% coverage with additionalProperties=false, so there is nothing for the description to disambiguate. Baseline 4 applies; no parameter claims are made that could mislead.

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 gives a specific verb (Generate) and resource (meeting briefs) with an explicit scope qualifier (ALL of today's meetings), which implicitly separates it from single-meeting siblings like get_meeting_brief and history-oriented ones like brief_with_history. It stops short of naming any sibling explicitly, so differentiation is inferred rather than stated.

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

Usage Guidelines3/5

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

"Perfect for morning prep" gives a use-case context, but there is no when-not guidance and no comparison against the many nearby alternatives (brief_with_history, get_outlook_brief, get_meeting_brief). The agent can infer the intended scenario but must guess about the alternatives.

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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