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Get growth

instagram_get_growth
Read-onlyIdempotent

Read growth time series for followers, media count, reach, views, and engagement from locally stored snapshots, including deltas between snapshots and no Instagram API request.

Instructions

Growth time series from locally stored snapshots (followers, media count, reach, views, engagement) with deltas between consecutive snapshots. Makes no Instagram request.

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": "instagram_get_growth"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoWindow in days (default 30).
sinceNoISO 8601 or YYYY-MM-DD; overrides days.
untilNoISO 8601 or YYYY-MM-DD; overrides days.
accountNoAccount alias; defaults to the configured default account.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely new behavior: data provenance is local snapshots with no network call, and values include deltas between consecutive snapshots. It does not mention what happens when no snapshots exist in the window or how stale the data may be, which is the main remaining behavioral 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 sentences, front-loaded with what is returned and immediately followed by the most decision-relevant constraint (no Instagram request). Every clause carries 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, the description does a reasonable job of sketching return content (metrics list plus deltas) and the data source. For a simple read-only tool with fully documented parameters this is close to sufficient; only the empty-snapshot / data-staleness case is unaddressed.

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 the baseline applies; the schema already explains days, since/until override behavior, and the account alias. The description adds only indirect meaning via 'consecutive snapshots', which hints at resolution of the returned series but does not tie it to parameter effects.

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 content: a growth time series of named metrics (followers, media count, reach, views, engagement) with deltas, sourced from locally stored snapshots. It implicitly separates itself from API-backed siblings like instagram_get_account_insights by noting 'Makes no Instagram request', though it does not name the sibling that produces snapshots (instagram_snapshot_insights).

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 phrase 'locally stored snapshots' and 'Makes no Instagram request' imply when this tool is appropriate (offline/low-cost historical trend), but the description never states when to prefer it over instagram_get_account_insights or to use instagram_snapshot_insights first to populate data. Usage is inferable rather than instructed.

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