OpenClueo MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'gets' suggestions, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns structured or free-text data, or how it handles missing history. For a tool with potential personalization and no annotations, this is a significant gap in transparency.

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: 'Get personality suggestions based on context and usage history.' It is front-loaded with the core action and resource, with no wasted words or redundancy. Every part of the sentence contributes directly to understanding the tool's function.

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 complexity of a tool that retrieves personalized suggestions based on history, with no annotations and no output schema, the description is incomplete. It doesn't explain what the suggestions look like (e.g., text, JSON), how personalization works, or error handling. For a tool with two parameters and behavioral nuances, this leaves critical gaps for an agent.

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?

The description mentions 'context and usage history,' which loosely maps to the 'context' and 'userId' parameters in the schema. However, with 100% schema description coverage, the schema already fully documents both parameters (e.g., 'context' as a string for scenarios like 'customer_email'). The description adds minimal value beyond the schema, so the baseline score of 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?

The description clearly states the tool's purpose: 'Get personality suggestions based on context and usage history.' It specifies the verb ('Get') and resource ('personality suggestions'), and distinguishes it from siblings like 'inject_personality' or 'list_personality_presets' by focusing on retrieval rather than application or listing. However, it doesn't explicitly differentiate from 'get_usage_analytics' or 'simulate_response', which slightly reduces 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 mentions 'based on context and usage history' but doesn't specify prerequisites (e.g., whether usage history must exist), exclusions, or direct comparisons to siblings like 'inject_preset_personality' or 'simulate_response'. This leaves the agent without clear decision-making criteria.

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