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

The description goes well beyond the annotations (readOnlyHint=false, openWorldHint=true) by disclosing detailed runtime behavior: 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit.' It also describes error/authentication flows (connect links, checkout links, retry logic) and side effects like 'without bloating the tool list.' No contradiction with annotations; the descriptive detail is exemplary.

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 dense, multi-line wall of text with no paragraph breaks, bullets, or headers, making it hard to scan. While every sentence carries useful information, the lack of structure hurts readability. It front-loads the core flow well ('Core flow: action=search...') but could benefit from separating the prompt library and permission details into distinct sections.

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?

For a tool with 23 parameters, no required fields, and no output schema, the description covers the primary workflows (search, describe, invoke, install, prompt library) comprehensively, including edge cases like authentication barriers and payment requirements. It also clarifies permission rules. However, some actions like `resume` are never mentioned, and the interaction between parameters (e.g., when `arguments` is required) is not explained, leaving minor gaps.

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?

With 0% schema description coverage, the description must compensate, and it does thoroughly explain the most critical parameter, `action`, listing all its enum values in prose and their purposes. Core parameters like `query`, `mcp_id`, `tool_id`, `arguments` are described contextually (e.g., 'search discovers MCPs by intent'). However, some parameters like `immediate`, `tier_slug`, `conversation`, and `report_context` remain unexplained, leaving gaps for an agent trying to use advanced features.

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 identifies the tool as 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It specifies core actions (search, describe, invoke) and distinguishes from sibling tools like report_bug by stating 'report_bug sends feedback' and 'request_mcp asks us to build a NEW MCP.' This is a specific verb+resource description that differentiates itself from alternatives.

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?

Explicit guidance is given on when to use which action: 'Use install only to make an MCP PERMANENT in the active toolkit' and 'prefer invoke for a single/occasional use.' It also clarifies when to use the prompt library functions (search_prompts, get_prompt, publish_prompt) and explains permission requirements for writes: 'require workspace owner/admin.' This exceeds typical guidance by providing clear decision rules.

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