likeV2(favorites) Tweet
get_base_apitools_likeV2likeV2 Group: Tweets. Billing per call: 1 Credits.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| ct0 | 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
D1.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of explaining behavior, but it only mentions billing cost and a category. It does not disclose that this is a mutating action, what credentials are needed, what side effects occur, or what response is returned. The billing note is minor behavioral context but insufficient.
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 very short, but brevity is not conciseness here because it omits essential information. The two sentences mostly restate the name and add billing details, leaving no space taken up by meaningful guidance. This is under-specification rather than well-structured conciseness.
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?
Given five unannotated parameters, no output schema, and an action likely involving authentication and side effects, this description is extremely incomplete. It does not explain what the tool does, what parameters mean, what the result format is, or any requirements. The tool cannot be safely selected or invoked based on this description alone.
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?
Schema description coverage is 0%, so the description must compensate for explaining the five string parameters, but it explains none of them. There is no clarification of what 'id' refers to, what ct0 and auth_token are for, how proxyUrl is used, or what resFormat expects. The parameter names alone are not enough for reliable invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description only restates the tool name ('likeV2') and labels it 'Group: Tweets' without stating what the tool does. It fails to say it likes/favorites a tweet or what resource it acts upon beyond the generic term 'Tweets'. This is closer to tautology than a clear functional purpose.
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?
No guidance is provided about when to use this tool versus alternatives like likeTweet, unlikeV2, or userLikeV2. The 'Group: Tweets' label is too generic to help an agent choose this tool over siblings. There are no usage contexts, prerequisites, or exclusions.
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.