wordpress_probe_upload_limits

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 clearly explains that the tool will attempt to use a companion plugin for more accurate results, and if not available, will do a best-effort from the WP REST index. It also states the caching period of 24 hours, which helps the agent understand the freshness of results. There is no contradiction with annotations (none exist).

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 very concise, using only three sentences. It front-loads the purpose with '[UNIFIED]' and the core action 'Probe a WordPress site for its effective upload limits'. Every sentence adds value: method, caching, and what limits are checked. No wasted words.

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 has only one parameter and no output schema, the description adequately covers its semantics. It explains the two possible probing methods, the caching behavior, and the list of limits checked. This is sufficient for an AI agent to use the tool correctly without additional information.

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 input schema only defines a 'site' parameter as a string with no description. The tool description adds meaning by specifying that the parameter represents a WordPress site URL, and that the tool probes that site for upload limits. This provides context beyond the raw schema, though it doesn't detail the expected format (e.g., must include protocol).

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: to probe a WordPress site for effective upload limits. It lists the specific PHP and WordPress limits checked (upload_max_filesize, post_max_size, etc.), making the function unambiguous. The tool name is descriptive, and the description adds specific detail, distinguishing it from sibling tools that deal with other aspects of WordPress or health metrics.

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 usage context by explaining it uses the airano-mcp-bridge companion plugin if available, or falls back to the WP REST index. It also mentions that results are cached for 24 hours per site, implying the tool can be used to check limits before uploads. It doesn't explicitly state when not to use it or suggest alternatives, but the context is clear enough for an AI agent to decide when it's appropriate.

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