get_misc_emojisReceive a full list of all twitter custom emojis with the hashtag, image and more. 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 are provided, so the description must carry the full burden. It discloses useful behavioral details such as 'full list' (indicating comprehensive output) and 'Billing per call: 1 Credits' (cost per invocation). However, it does not explicitly state read-only nature, potential response size, rate limits, or authentication requirements. This leaves some behavioral ambiguity.
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?
The description is highly concise with three short sentences, each providing distinct useful information: the main purpose, the grouping, and the billing cost. There is no fluff or repetition, and the main action is front-loaded.
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?
For a zero-parameter tool with no output schema, the description is fairly complete: it states what is returned (hashtag, image, and more) and the cost per call. The phrase 'and more' is a bit vague, but given the simplicity of the tool, the description covers essential expectations adequately.
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?
This tool has zero parameters, so the schema baseline is 4. The description adds no parameter-specific details since there are none to explain. It correctly avoids inventing parameters, and the schema is fully covered with an empty object, so the baseline score is appropriate.
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 tool's function: 'Receive a full list of all twitter custom emojis with the hashtag, image and more.' This is a specific verb (Receive/Get) targeting a distinct resource (Twitter custom emojis), and the title reinforces the scope. It distinguishes from sibling misc tools like get_misc_locations and get_misc_subtitles.
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?
The description implies usage: if you need Twitter custom emojis, this is the tool. It also mentions the group 'Utilities/Misc' but does not explicitly state when to use this over alternatives or provide any exclusions. No sibling comparisons are given, so the guidance remains implicit rather than explicit.
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.