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content-engine-mcp

content-engine-mcp

by DevMandalia

get_cadence_status

Retrieve cadence reminders and current status as data, enabling an agent to decide when to schedule or send content tasks because the server cannot self-schedule.

Instructions

Cadence reminders as data. This server cannot self-schedule.

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": "get_cadence_status"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It does disclose one genuinely useful behavioral limit (no self-scheduling), but says nothing about freshness, read-only nature, error conditions, or what the returned data represents.

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?

Two very short sentences with no filler and the constraint placed second, but the first sentence is a fragment that reads more like a tagline than a statement of behavior, so brevity comes at the cost of clarity.

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?

There is no output schema, so the description is the only place an agent can learn what this returns; "as data" gestures at structure without specifying it. For a zero-param read tool this leaves the return value essentially undefined.

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 zero parameters, so the baseline applies; there is no parameter semantics for the description to explain.

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

Purpose2/5

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

"Cadence reminders as data" restates the name (cadence → cadence reminders) without a clear verb or object of the retrieval. It never says whether it returns reminder schedules, pending reminders, or cadence configuration, so an agent cannot distinguish this from a status-check of any other sibling.

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?

The only guidance is a negative constraint ("This server cannot self-schedule"), which tells the agent what not to expect but not when to call this tool versus siblings like get_setup or get_seed. No positive usage condition is given.

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