get_v2_UserMediaUser Media Group: User. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Use the User By Screen Name endpoint to find the ID from a username. | |
| count | No | Number of results | |
| cursor | No | Cursor for other results |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It does not mention side effects, required permissions, rate limits, or any operational details. The only added info is billing cost, which does not inform behavioral expectations.
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 short, but it is not front-loaded with useful content. The billing phrase is irrelevant to tool selection and execution. It is a waste of space, so while it is concise in word count, it is not effective or well-structured.
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 tool with 3 parameters and no output schema, the description should explain its purpose and return behavior. The given description is completely inadequate, offering no help in understanding what 'User Media' entails or how to use it. Sibling tools like get_v2_UserTweets are not differentiated.
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?
Schema coverage is 100%, and each parameter (id, count, cursor) has a description. The tool description adds no parameter meaning, but the schema already provides sufficient detail. Hence the baseline 3 applies; the description's failure to add value does not lower it further.
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 'User Media Group: User. Billing per call: 1 Credits.' does not state what the tool does. It only provides a grouping and billing note. The verb and resource are absent, making the purpose ambiguous. It falls short of even a tautology, as it fails to mention any action or data retrieval.
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?
No guidance is given on when to use this tool versus alternatives. There is no context about scenarios, exclusions, or selection criteria among the many sibling tools. The description is entirely silent on usage.
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.
Several tools appear to do the same thing, such as get_v1_1_Followers vs get_v2_Followers and get_v2_Tweet vs get_v2_TweetDetail. The descriptions are too brief to clarify differences, and multiple user lookup tools (get_v1_1_Users, get_v2_UserByRestId, etc.) create confusion.
Naming is inconsistent, mixing camelCase (get_ShortUrl), snake_case (get_email_search_by_username), and version prefixes with varying formats (get_v1_1 vs get_v2). No uniform verb_noun pattern is followed.
With 32 tools, the server is overloaded, especially given many redundant variations across API versions. The count exceeds the 25-tool threshold for too many tools, and many could be consolidated.
The server is entirely read-only (all tools are GET), missing write operations like posting tweets, following users, or sending direct messages. This is a significant gap for a Twitter server, and even read coverage has redundancies rather than comprehensive distinct endpoints.