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Get User Profile

get_user_profile
Read-only

Get an Instagram user's profile with optional extra sections: posts, reels, tagged, followers, and following.

Instructions

Get an Instagram user's profile.

Args: username: Instagram username (e.g., "instagram", "natgeo") ctx: FastMCP context for progress reporting sections: Comma-separated list of extra sections to scrape. The main profile page is always included. Available sections: posts, reels, tagged, followers, following Examples: "posts,reels", "tagged", "followers,following" Default (None) scrapes only the main profile page.

Returns: Dict with url, sections (name -> raw text), and optional references. Sections may be absent if extraction yielded no content for that page. Includes unknown_sections list when unrecognised names are passed. The LLM should parse the raw text in each section.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionsNo
usernameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds meaningful behavioral details: it scrapes extra sections, returns raw text, sections may be absent if no content, and unknown sections are surfaced. It does not contradict annotations and offers extra nuance about the scraping behavior that the agent would not otherwise know.

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?

The description is well-structured with an Args/Returns format, but it includes a `ctx` parameter that is not present in the input schema, which adds slight confusion. Overall, it is appropriately sized, front-loaded with the core purpose, and every sentence contributes meaning.

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?

The tool has an output schema and the description still explains return structure (dict with url, sections, references) and failure modes (sections may be absent, unknown_sections). It lacks details on rate limits or pagination for large lists like followers/following, but given the read-only and open-world hints, the description is sufficiently complete for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is bare (no descriptions), so the description's parameter explanations are essential. It clarifies `username` with examples, explains `sections` values and defaults, and documents the `ctx` parameter. This fully compensates for the 0% schema coverage and adds context that the schema cannot convey.

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 opens with 'Get an Instagram user's profile,' a specific verb+resource phrase that clearly distinguishes this tool from sibling tools like get_user_posts or get_user_reels. It also specifies the primary scope (main profile page) and optional sections, leaving no ambiguity about what is retrieved.

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 description provides clear instructions on how to use the `sections` parameter and includes examples, plus notes about defaults and unknown_sections. However, it does not explicitly state when to choose this tool over siblings like get_user_posts or get_user_reels. The usage context is implied by the tool's purpose but no alternatives or exclusions are mentioned.

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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