Stacks Clarity 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 mentions the tool generates post-conditions but doesn't describe what that entails operationally—e.g., whether it's a read-only calculation, if it requires network access, potential errors, or output format. For a tool with 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 concise and front-loaded with two clear sentences: the first states the purpose, and the second adds context. There's no wasted text, making it efficient. However, it could be slightly more structured by explicitly separating purpose from usage, preventing a perfect score.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the purpose and basic usage but lacks details on behavior, output, or integration with sibling tools. Without annotations or an output schema, more context would be helpful for an AI agent to use it 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%, so the input schema already documents all three parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, such as examples or edge cases. This meets the baseline score of 3, as the schema does the heavy lifting, but the description doesn't enhance understanding.

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: 'Generate an STX post-condition for STX transfers.' It specifies the verb ('generate') and resource ('STX post-condition'), and adds context about use cases ('Essential for payment and fee transactions'). However, it doesn't explicitly differentiate from sibling tools like 'generate_fungible_post_condition' or 'generate_non_fungible_post_condition', which prevents a perfect score.

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 implied usage guidance by stating the tool is 'Essential for payment and fee transactions,' which suggests when to use it. However, it doesn't explicitly mention when not to use it or name alternatives among the many sibling tools, such as the other post-condition generators. This leaves some ambiguity about tool selection.

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