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Twitter Tweet Details

social_twitter_tweet
Read-only

Retrieves detailed information about a specific tweet by URL, including the author's profile and engagement metrics. Returns rest_id, full_text, views count, favorite_count, retweet_count, reply_count, bookmark_count, quote_count, created_at, source, and media entities. Supports a trim parameter for a lighter response. Completed lookups cost at least 10 Nexscope credits. Actual cost depends on the operation and requested options. Repeated requests may purchase data again. Twitter Tweet Details API View Pricing Get detailed information about a specific tweet including engagement 1 credit per request If we have a response in the cache that is this many days old or newer, return the cached response (0 credits, with "cached": true and a "cached_at" timestamp). Otherwise, scrape a live result (1 credit). See the Caching page for details.

Input Schema

NameRequiredDescriptionDefault
urlYesTweet URL
trimNoSet to true for a trimmed down version of the response
cache_max_ageNoIf we have a response in the cache that is this many days old or newer, return the cached response (0 credits, with "cached": true and a "cached_at" timestamp). Otherwise, scrape a live result (1 credit). [See the Caching page for details.](https://docs.scrapecreators.com/caching)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and destructiveHint=false, but the description adds real substance: the returned field list, the trim option for a lighter payload, and the caching contract ('cached': true with a cached_at timestamp, 0 credits vs a live scrape). The cost statements are internally inconsistent ('at least 10 Nexscope credits' versus '1 credit per request'), which muddies billing disclosure even though the caching semantics remain clear.

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

Conciseness2/5

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

The first two sentences are well front-loaded, but the rest is pasted marketing and documentation boilerplate ('Twitter Tweet Details API View Pricing ... 1 credit per request') and a verbatim duplicate of the schema's caching paragraph. The conflicting credit figures (10 vs 1) further reduce clarity rather than adding it.

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?

For a read-only lookup with no output schema, the description is largely complete: it enumerates return fields, explains the trim tradeoff, and documents the cache path and its zero-credit behavior. Missing pieces are minor — no error/not-found behavior and no clarification of what trim actually strips, plus the unresolved credit discrepancy.

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 url, trim, and cache_max_age are already documented, and the description's cache paragraph is copied verbatim from the cache_max_age schema entry rather than adding meaning. The only modest addition is tying 'trim' to the enumerated return fields, which hints at what a trimmed response omits without specifying it.

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?

The description states a specific verb and resource ('Retrieves detailed information about a specific tweet by URL') and enumerates the returned fields, so the agent knows exactly what it gets. It does not name sibling alternatives such as social_twitter_search_posts or social_twitter_user_tweets, so differentiation by URL-vs-search is left implicit.

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?

Usage is implied by the single-tweet-by-URL framing plus the caching condition ('if we have a response in the cache that is this many days old or newer'), which tells the agent how to control cost. However, no sibling tool is named and there is no explicit when-not guidance, so the agent must infer that this is for one known tweet URL rather than discovery.

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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