Location (for trends)
get_misc_locationsThis gives you a list of all available locations. Group: Utilities/Misc. Billing per call: 1 Credits.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
get_misc_locationsThis gives you a list of all available locations. Group: Utilities/Misc. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears the transparency burden. It implies a read-only list operation and discloses billing cost (1 credit), but it does not describe response shape, pagination, or other behavioral details. For a simple zero-parameter list call, this is acceptable but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: the first delivers the main purpose, and the second packs group and billing metadata. No filler; the structure is appropriate for such a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema or annotations, the description would benefit from stating what each returned location contains or how it relates to get_trends_locationId. For a zero-parameter, read-only listing, it is minimally complete but leaves output interpretation to the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so parameter semantics are trivially satisfied and the baseline is 4. The description rightly adds no parameter-level detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('gives you a list') and the resource ('all available locations'), distinguishing it from the misc emoji/subtitle utilities. It does not explicitly tie the list to trend location IDs, but the title provides that hint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit when-to-use guidance, nor any mention of using this list to populate or choose IDs for get_trends_locationId. The 'Group: Utilities/Misc' metadata and billing line convey context but not selection rules.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct data types, but there is notable overlap: get_search_searchTerm vs post_search_searchTerm and get_tweet_tweetId vs post_tweet_tweetId are functional duplicates, and the three followings variants (get_user_userId_followings, _basic, _ids) have unclear boundaries. This creates ambiguity for an agent trying to select the right tool.
Tool names mix HTTP method prefixes (get_, post_) with resource_parameter structures, and camelCase is embedded in parameters (searchTerm, tweetId, tweetsAndReplies). The pattern is not uniform (e.g., get_user_by_username_username vs get_user_usernames_to_ids), making the naming feel ad hoc and hard to predict.
With 23 tools, the set is on the heavier side. Many tools are redundant (GET/POST duplicates) or overly granular (three followings endpoints), padding the count without adding distinct capabilities. A leaner set of 15-18 tools would be more appropriate for the read-only Twitter data scope.
The server covers the core read-only Twitter data surface well: user info, tweets, media, followers/followings, likes, search, trends, and miscellaneous utilities. The only notable gap is the lack of a direct endpoint for listing a user's followers' details (though that could be composed), and no ability to post or interact, which aligns with the apparent purpose.