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Twitter Agent by Nova (CIVAI)

get_mentions

X / Twitter: get mentions

Input Schema

NameRequiredDescriptionDefault
countNoHow many mentions (1-50)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure, yet it says nothing about ordering (recency vs relevance), pagination, authentication requirements, or rate limits. Only the weak implication of 'get' that this is a read operation is conveyed. This is a significant gap for a network-backed retrieval tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short label with zero waste, but it also earns little; brevity here reflects under-specification rather than disciplined front-loading. It is appropriately sized only in the sense that there is almost no content to organize.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations, no output schema, and no parameter guidance in the description, an agent cannot know what the response looks like, whether mentions are of the authenticated account, or how results are ordered. For a simple one-parameter tool this is still notably incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the single parameter ('count', 1-50) is fully documented in the schema. The description adds nothing beyond the schema, but with full coverage the baseline of 3 applies. It does not clarify default count or what happens when count is omitted.

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 names a verb and resource ('get mentions') and prefixes the platform ('X / Twitter'), so the resource is identifiable. But it is essentially a restatement of the tool name with no additional specificity about whose mentions or what subset is returned. No sibling deals with mentions, so distinguishing from siblings is not a major need, keeping this at a minimum-viable 3.

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 such as search_tweets or get_thread, nor any stated prerequisites (e.g. authenticated user context). The only implied usage comes from the name itself. This matches the 'no guidance' level.

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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