instagram_insightsInstagram engagement rate calculator. Engagement rate (mean and median), posting cadence, format mix, best posting hours (UTC) and a percentile against the Instagram Benchmarks report, from the latest 12 posts. Pinned posts are excluded.
Cost: 2 credits.
| Name | Required | Description | Default |
|---|---|---|---|
| username | Yes | Instagram handle, with or without @. A profile URL also works. |
Changes observed during successful MCP inspections.
Input schema / properties / user_idRemoved value: -{
- "description": "Numeric Instagram user id. Pass this or username.",
- "type": "string"
-}Input schema / properties / username / descriptionPrevious value: -"Instagram handle, with or without @. A profile URL also works. Pass this or user_id."New value: +"Instagram handle, with or without @. A profile URL also works."Input schema / requiredPrevious value: -[]New value: +[
+ "username"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds genuinely useful context beyond that: the analysis window (latest 12 posts), the pinned-post exclusion rule, and a 2-credit cost. It does not cover caching, rate limits, or failure modes, but with annotations present this is above the bar.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the identity and outputs, followed by the scope/exclusion caveats and cost. No filler or restated name/title.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 carries the burden of describing returns, and it does so concretely (engagement mean/median, cadence, format mix, best hours, percentile). For a one-parameter read tool it is nearly complete; only error/empty-account behavior is unaddressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With a single parameter and 100% schema description coverage, the schema fully documents the username input including '@' handling and URL acceptance. The description adds no parameter detail beyond that, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific analytic resource (Instagram engagement rate) and enumerates exactly what is computed: mean/median engagement, posting cadence, format mix, best posting hours, and a benchmark percentile. It is clearly distinguishable from generic siblings like instagram_profile or instagram_posts in substance, though it never names an alternative to route against.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied (reach for this when you want engagement/cadence analytics) and the 'latest 12 posts' scope is stated, but there is no explicit when-to-use vs when-to-use-something-else guidance relative to siblings such as instagram_profile or instagram_posts. The cost note hints at a selection tradeoff but does not spell one out.
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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