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Comments under an Instagram post

instagram-comments
Read-only

Instagram comments API for AI agents: send the URL of a post or reel and get its comments as JSON: text, time, likes and reply count. Up to 100 comments per call. The commenters' names and handles are not returned. Pay per call in stablecoins; comments you paid for but did not get are refunded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesURL of an Instagram post or reel, e.g. https://www.instagram.com/p/DdG4RIxIPyf/
limitNonumber of comments wanted, 1 to 100 (default 20). A larger value is lowered to 100 and 0 or a negative one means the default; the quote follows the value used.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnly/openWorld annotations, it discloses a hard cap of 100 comments per call, that commenter names and handles are deliberately not returned, and an unusual payment model (pay-per-call in stablecoins with refunds for undelivered comments). These are behavioral traits an agent could not infer from annotations or schema.

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?

Three tight sentences: purpose and invocation first, then result shape, then constraints and payment. Every sentence carries information an agent needs and none repeats the schema.

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?

With no output schema, the description compensates by naming the returned fields (text, time, likes, reply count) and flagging the missing commenter identity. Combined with the cap and refund behavior, an agent has everything needed to call this correctly and interpret the result.

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% and both parameters are fully documented in the schema, including default, min/max, and clamping behavior. The description only echoes the 100-comment cap, adding no syntax beyond what the schema already provides, so the baseline 3 applies.

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

Purpose5/5

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

The description states a specific verb+resource: send a post/reel URL and receive its comments as JSON. The title and resource scope (comments under a post) make it clearly distinct from the sibling instagram tool (post data) and from tiktok-comments/youtube-comments, so an agent can pick it without opening the schema.

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?

It implies when to use it ('send the URL of a post or reel and get its comments') but offers no explicit when-not or alternative routing, e.g. to the sibling 'instagram' tool for post metadata. Usage context is present but entirely inferred.

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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