Haloscan MCP Server

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. It describes a read operation ('obtenir') but doesn't cover critical aspects like rate limits, authentication needs, data freshness, or what the output looks like (since no output schema exists). For a tool with two required parameters and no annotations, this leaves the agent guessing about 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 a single, efficient sentence in French. It's front-loaded with the core purpose and wastes no words. However, it could be more structured by explicitly stating the tool's scope or output, but given its brevity, it earns a high score for conciseness.

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 the tool's complexity (comparing domains and competitors for keyword differences), lack of annotations, no output schema, and vague purpose, the description is incomplete. It doesn't explain what 'domaines' are, how the difference is calculated, or what the result includes. For a tool with two required parameters and no structured output, more context is needed to guide the agent effectively.

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 100%, with both parameters documented: 'input' as 'Seed keyword' and 'competitors' as 'Specific data fields to request'. The description adds no additional meaning beyond the schema—it doesn't clarify what 'domaines' are, how competitors relate to them, or the format of the keyword difference. With high schema coverage, the baseline is 3, but the description doesn't compensate for potential ambiguities.

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 states the tool's purpose in French: 'Obtenir la différence de mots-clés entre les domaines et leurs concurrents' (Get the keyword difference between domains and their competitors). It specifies a verb ('obtenir') and resource ('différence de mots-clés'), but it's vague about what 'domaines' refers to and doesn't clearly differentiate from sibling tools like get_domains_competitors or get_domains_keywords. The purpose is understandable but lacks specificity.

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. It doesn't mention prerequisites, context, or exclusions. Given many sibling tools (e.g., get_domains_competitors, get_domains_keywords), the agent must infer usage without help. This is a significant gap for tool selection.

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