axure-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 mentions building a prompt but fails to describe key behaviors: what the tool does internally (e.g., crawling, OCR processing), potential side effects (e.g., network requests, data extraction), error handling, or output format. This is inadequate for a tool with 11 parameters and complex functionality.

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, front-loaded sentence that efficiently conveys the core purpose without unnecessary words. Every part of the sentence ('Build an AI-ready summary prompt from a public Axure link') contributes directly to understanding the tool's function, making it appropriately concise and well-structured.

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 (11 parameters, no annotations, no output schema, low schema coverage), the description is incomplete. It lacks details on behavior, parameter usage, output expectations, and error conditions. For a tool with such rich input options and no structured guidance elsewhere, the description fails to provide sufficient context for effective agent use.

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 low at 18%, with only the 'url' parameter having a description. The tool description does not compensate by explaining the semantics of other parameters like 'focus', 'timeoutMs', or OCR-related options. It adds no meaningful context beyond what the minimal schema provides, leaving most parameters undocumented in both schema and description.

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 action ('Build') and the target resource ('AI-ready summary prompt from a public Axure link'), making the purpose understandable. It distinguishes from sibling tools like 'axure_fetch' and 'axure_health' by focusing on prompt creation rather than fetching or health checks. However, it lacks specificity about what constitutes an 'AI-ready summary prompt' (e.g., format, content structure).

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?

No explicit guidance is provided on when to use this tool versus alternatives like 'axure_fetch' or 'axure_health'. The description implies usage for generating prompts from Axure links but doesn't specify scenarios, prerequisites, or exclusions (e.g., only for public links, not for private ones). 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.