get_base_apitools_unlikeTweetsee details https://developer.x.com/en/docs/twitter-api/v1/tweets/post-and-engage/api-reference/post-favorites-destroy Group: Tweets. Billing per call: 1 Credits.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| ct0 | No | ||
| proxyUrl | No | ||
| resFormat | No | ||
| auth_token | No |
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?
No annotations are provided, so the description must carry behavioral disclosure. It only mentions 'Billing per call: 1 Credits' which is a basic constraint, but does not disclose what the tool does beyond the title. No mention of side effects, authentication requirements, or response behavior.
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 very short, but it is insufficiently informative. The external link provides some detail but is not helpful for an agent that needs to invoke the tool without external lookup. It is not concise in the sense of conveying essential information.
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 are 5 parameters with no descriptions, no annotations, and no output schema, the description is grossly inadequate. An agent cannot correctly invoke this tool without knowing parameter formats, required authentication tokens, and the expected behavior. The link is external and not part of the description.
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 description coverage is 0%. The description does not explain any parameter semantics. Parameters like id, ct0, proxyUrl, resFormat, auth_token are not described. The only hint is the title, which implies 'id' is the tweet ID, but it is not explicit.
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 is essentially a URL link and a group label, but the title 'unlike(unfavorites) Tweet' clearly states the action (unlike) and resource (Tweet). It distinguishes from sibling tools like likeTweet and unlikeV2 through the title, though the description itself is not descriptive.
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 on when to use this tool vs alternatives. The description provides only a link to external documentation and a group label. There is no mention of when to choose this over unlikeV2 or other liking/unliking tools.
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.
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 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.
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.
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.