x-ai-mcp

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

No annotations are provided, so the description carries full burden. It mentions 'Use Grok to analyze', implying an external service or AI, but doesn't disclose behavioral traits like rate limits, authentication needs, data freshness, or what 'analyze' entails (e.g., returns structured insights vs. raw data). This is a significant gap for a tool with no annotation coverage.

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 front-loaded with the core purpose, followed by a concise parameter explanation. Every sentence earns its place, with no wasted words. It's appropriately sized for a single-parameter tool.

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 1 parameter, no annotations, but an output schema exists, the description is minimally adequate. It covers the purpose and parameter semantics, but lacks behavioral context (e.g., how analysis is performed, limitations). The output schema likely handles return values, so that gap is mitigated, but overall completeness is moderate.

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%, but the description compensates by explaining the 'username' parameter: 'X username (without @)'. This adds crucial semantics beyond the bare schema, clarifying format. With only 1 parameter, this is sufficient for a high score, though not perfect as it doesn't cover edge cases.

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 clearly states the tool's purpose: 'analyze an X account' with specific aspects like 'posting patterns, key topics, influence, and recent activity'. It distinguishes from siblings like x_user_info (which might provide basic info) or x_user_tweets (which lists tweets), but doesn't explicitly contrast them, so it's not a perfect 5.

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?

The description provides no guidance on when to use this tool versus alternatives like x_user_info or x_analyze_topic. It mentions 'Use Grok to analyze', but this is vague and doesn't specify context or exclusions. The agent must infer usage from the purpose alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.