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Get posting frequency vs engagement

get_posting_cadence
Read-onlyIdempotent

How many posts per week each network gets and the engagement rate at that cadence — the data behind "should we post more or less?".

Input Schema

NameRequiredDescriptionDefault
daysNoWindow in days (default 30). Up to 365 days of history are available.
accountIdNoRestrict to one account (Ignix account id). Omit for all of them.
workspaceIdNoWorkspace to work on (an id from list_workspaces). Not needed when this connection is tied to one workspace, or when you pass an account: the account's workspace is used.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so safety and idempotency are covered. The description adds useful context about the shape of the returned data (per-network frequency paired with cadence-level engagement) but says nothing about history limits, aggregation behavior, or permissions.

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?

A single front-loaded sentence that leads with the returned data rather than restating the name. Slightly awkward with the em-dash plus embedded quoted question, but no wasted sentences.

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, the description carries the return-value burden and does describe the two core outputs (posts-per-week per network, engagement rate at that cadence). Combined with full schema coverage and safety annotations, an agent has enough to call it correctly, though aggregation granularity and history bounds are left implicit.

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 days, accountId, and workspaceId are each documented in the schema with defaults and fallback rules. The description adds no parameter meaning beyond that, so the baseline 3 applies.

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 names a specific resource and pairing: posts per week per network plus the engagement rate at that cadence. This is clearly distinct from generic siblings like get_engagement_trend or get_analytics, but it never names a sibling explicitly, so differentiation is implied 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?

The framing question "should we post more or less?" implies the decision context in which to reach for this tool, but there is no explicit when-to-use/when-not-use guidance and no routing to alternatives such as get_best_times or get_engagement_trend.

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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