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Glama

instagram-scraper

Checking the spent

get_requests

Checking the spent status Billing per call: 1 Credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.1/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It mentions 'Billing per call: 1 Credits', which hints at cost but doesn't clarify what 'spent status' means, whether it's a read-only check, or any side effects. The term 'spent' is ambiguous.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short, but it is also under-specified. 'Checking the spent status' is concise but not informative. The billing note is brief but adds a cost context. It earns a 3 because it's not wasteful, but it doesn't use its brevity well.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters, no output schema, and no annotations, the description should explain what 'spent status' means, what the response looks like, and what the tool is for. It fails to provide any meaningful context, making it essentially a stub.

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

Parameters4/5

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

The input schema has zero parameters, and schema description coverage is 100%. With no parameters, the description has little to add; the baseline for 0 params is 4. The description does not explain any implicit inputs, but that is acceptable given no params.

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

Purpose2/5

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

The description says 'Checking the spent status' which is vague and tautological with the title 'Checking the spent'. It does not specify what resource is being checked or how it differs from siblings like get_info or get_server.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus the many sibling tools. There is no mention of use cases, alternatives, or conditions.

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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TDQS

C2.4/5.0
Disambiguation2/5

Many tools have overlapping or near-identical purposes (e.g., get_posts vs get_posts_username, get_reels_posts vs get_reels_posts_username). The distinction between get_post_info, get_post_info_v2, get_reel, and get_tv_info is unclear from descriptions alone. This will cause frequent misselection.

Naming Consistency2/5

Naming is inconsistent: suffixes like '_username', '_hd', '_v2', '_id' appear sporadically, and the same resource type is named differently (e.g., 'posts' vs 'post_info' vs 'reels_posts' vs 'tv_posts'). Some tools are meta (get_requests, get_server) and deviate from the data-focused pattern. Overall, no clear naming convention.

Tool Count2/5

With 40 tools, the set is overly large for an Instagram scraper. Many tools are near-duplicates differing only by input type (ID vs username), which could be consolidated. The count far exceeds the typical 3-15 range and feels bloated, though not extreme.

Completeness4/5

The tool set covers a comprehensive range of Instagram data: user info, posts, reels, TV, stories, highlights, comments, likes, followers, followings, hashtag/location/music search, and even server status. Despite some vague tools (get_additional_info, get_basic_engagement), it appears functionally complete for the domain.

Resources