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twitr.sh

by sh.twitr

x_radar

Trending topics and breaking stories across tech, dev, science, business, culture, politics, and entertainment — aggregated from multiple public sources with regional and time-window filters. Flat sub-cent price per call; the cheap first stop for what is happening right now.

Guidance: Optional filters: category, region, hours (lookback), limit, source. Use report.next_cursor via after for the next page. Flat floor price per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNoPagination cursor.
hoursNo
limitNo
regionNo
sourceNoTrend source filter.
categoryNoTopic category filter.

Schema Changelog

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

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided. The description adds cost info ('flat sub-cent price') and pagination behavior ('use report.next_cursor'). It does not mention auth needs, rate limits, or whether the tool is read-only. For a read tool, this is adequate but could include more about data freshness or limits.

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 two short paragraphs: the first states purpose and cost, the second gives parameter and pagination guidance. It is mostly concise, but the price mention could be integrated more smoothly. No redundant sentences.

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?

Given the tool has 6 optional params, no output schema, and no annotations, the description covers the main behavioral aspects (cost, filtering, pagination). It could be improved by mentioning the structure of returned items or typical response format, but it is fairly complete for its purpose.

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 schema has 6 params with 50% description coverage. The description adds value by indicating all filters are optional and grouping them, and explaining the 'after' parameter for pagination. This compensates for the missing schema descriptions on hours, limit, and region.

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 clearly states it provides 'trending topics and breaking stories' across multiple categories, with specific sources and filters. This distinguishes it from sibling tools like x_read (reading content) or x_search (searching). The verb 'aggregates' and resource 'topics/stories' are specific.

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

Usage Guidelines4/5

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

The description frames it as 'the cheap first stop for what is happening right now', implying it's for quick trend overviews. It lists optional filters and pagination. However, it does not explicitly say when not to use it or compare to alternatives like x_search or x_monitor.

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

A4.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (write, read, search, monitor, compose, etc.), but some overlaps exist: x_read includes trending topics while x_radar is dedicated to trends, and x_timeline provides engagement lists that overlap with x_extract's extractors. Descriptions help differentiate them, but an agent might initially confuse the boundary between x_read, x_search, and x_timeline for tweet retrieval.

Naming Consistency4/5

All tool names share the x_ prefix and are single words, but mix verb forms (read, search, write, compose, extract, monitor) with noun forms (draws, radar, inbox, lists, profile, timeline). The convention is predictable and uniformly lowercase, but a fully consistent verb_noun or noun-only pattern would be clearer. Minor deviation: x_communities vs x_community are nearly identical and refer to reading vs managing.

Tool Count5/5

14 tools is well within the ideal 3-15 range and each tool covers a distinct functional area of X/Twitter: reading, writing, searching, monitoring, extracting, composing, community management, etc. The count feels appropriate for the broad scope of the server, neither bloated nor thin.

Completeness5/5

The tool surface covers the major X/Twitter interactions comprehensively: fully capable read (x_read, x_search, x_timeline), write (x_write, x_profile), community and list operations, real-time monitoring, bulk extraction, direct messaging, media, trends, and even AI-assisted composition and giveaways. Obvious gaps are minimal, such as no list creation/management commands, but the core lifecycle of tweets, users, communities, and accounts is well covered.

Resources