competlab-mcp-server

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

No annotations provided, so description carries full disclosure burden. Declares 'Read-only' safety trait and crucial resource cost ('3 prompts across 3 LLMs = 9 total AI queries'). Details return structure comprehensively (scores, mention rates, provider breakdowns). Minor gap: no mention of caching, staleness, or error conditions.

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?

Exceptionally information-dense yet structured. Front-loaded with purpose, followed by unique value proposition, return payload details, resource costs, usage guidance, and safety declaration. Every sentence conveys distinct value without redundancy.

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?

No output schema exists, but description comprehensively documents returns (composite scores, mention rates, per-provider breakdowns, rankings, analysis). Covers the complex multi-LLM query behavior. Minor gap: could clarify data freshness or caching behavior for 'latest' scores.

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 coverage is 100% (projectId fully described in schema with pattern and source hint). Description does not add parameter semantics beyond schema, but with complete schema documentation, baseline 3 is appropriate.

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?

Clear specific verb 'Get' + resource 'AI Visibility scores' + scope 'all competitors'. Explicitly distinguishes from siblings by stating 'Use this for the current snapshot; use get_ai_visibility_history for past checks or get_ai_visibility_trend for time-series data', eliminating ambiguity about which tool to select.

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?

Provides explicit when-to-use guidance ('current snapshot' vs alternatives) and names specific sibling tools for different use cases (history for past checks, trend for time-series). Also includes resource-cost guidance ('9 total AI queries') to inform invocation decisions.

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