AI Takeover Tracker MCP Server

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

No annotations are provided, so the description carries full burden. It discloses key behavioral traits: returns multiple variants with different risk scores, and highlights significance of score differences (e.g., Staff Accountant 45.6 vs Business Analyst 32.1). However, it doesn't mention response format, pagination, or error handling.

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?

Two sentences with zero waste: first defines purpose with concrete example, second provides explicit usage guidelines with rationale. Front-loaded with core functionality, and every sentence adds essential value.

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 with full schema coverage and no output schema, the description is largely complete: explains purpose, usage, and output implications (variants with risk scores). It could mention response structure or error cases, but covers core context well for a read-only lookup tool.

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% (parameter 'identifier' described as 'Occupation slug or SOC code'), so baseline is 3. The description adds no additional parameter semantics beyond what the schema provides, focusing instead on usage context and output implications.

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: 'Get specialization variants for an occupation' with specific examples (e.g., 'accountants' has variants like Tax Accountant). It distinguishes from siblings by focusing on occupation variants rather than general occupation data (get_occupation_risk), tasks (get_occupation_tasks), or searches (search_occupations).

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?

Explicitly states when to use: 'ALWAYS use this when a user asks about a specific job title that might be a variant of a broader occupation.' It provides a clear alternative context (risk score differences matter) and distinguishes from other tools by emphasizing variant-specific data.

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