get DMS List
get_base_apitools_getDMSListV2get DMS List Group: DMS. Billing per call: 1 Credits.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| ct0 | No | ||
| apiKey | No | ||
| max_id | No | ||
| proxyUrl | No | ||
| resFormat | No | ||
| auth_token | No |
x-twitter
by com.jojapi
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
C2/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only mentions billing credits, which is not a behavioral aspect like auth requirements, rate limits, or side effects. The operation's read-only nature is implied by 'get' but never explicitly stated.
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 description is extremely short, but this is under-specification rather than effective conciseness. The group and billing information add little value for tool invocation, while essential details are missing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With six undocumented parameters, no output schema, and no annotations, the description is grossly insufficient. It fails to explain what the tool returns, how to configure parameters, or when to use it, making it nearly impossible for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has six parameters with zero description coverage, and the description adds no meaning to any of them. Parameters like ct0, max_id, proxyUrl, and resFormat remain completely opaque, forcing the agent to guess their formats and purposes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'get DMS List,' clearly indicating this tool retrieves a list of direct messages. However, it lacks specifics on whether it returns sent/received DMs or pagination, and it does little to distinguish itself from sibling tools like getDMS or getDMSInitIdV2.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description only mentions group and billing, not any selection criteria, prerequisites, or scenarios.
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
D1.4/5.0
Disambiguation1/5
The set is full of confusing variants such as get_/post_ prefixed duplicates of the same endpoints, competing V1/V2 versions of the same action (e.g., followersList vs. followersListV2), and poorly described tools like CommunitiesSearchV2 and getCt0 that give no clear unique purpose. Agents would frequently need to guess between similar tools for a single task.
Naming Consistency1/5
Naming is chaotic, mixing camelCase (getDMS, likeV2), PascalCase (CreateNoteTweet, CommunitiesMemberV2), and inconsistent prefixes (gettools_*, get_*, post_*) with duplicated operations. The 'get_/post_' prefixes appear to indicate API method rather than action, but they are applied inconsistently, with some tools appearing under both and others only once. There is no predictable verb_noun pattern throughout.
Tool Count1/5
With 107 tools, the server is extremely large, far exceeding the 50+ threshold for extreme mismatch, and this count is inflated by duplicates (many get_/post_ twins) and overlapping V1/V2 variants. Even the unique tool set is likely around 60-70, which is still an unwieldy surface for an agent to negotiate. This severely disrupts coherence.
Completeness3/5
The tool set covers most core Twitter/X domains: tweets, likes, retweets, follows, DMs, search, communities, lists, and profile management. However, it is cluttered with duplicates and lacks some obvious pieces like mute/unmute operations or a direct 'update tweet' action, and several tools appear to be thin wrapper variations of the same endpoint. Coverage is broad but not cleanly organized.