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

Annotations only state readOnlyHint=false and no destructiveness hint, but the description adds rich behavioral context: invoke works even when the MCP is not installed, runs one-off without bloating the toolkit, returns connect/checkout links for auth/billing, and writes require workspace owner/admin. No contradiction with annotations.

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 long but every sentence earns its place, covering many actions and edge cases without padding. It front-loads the core purpose and uses a flow-based structure that aids comprehension, though it could be more scannable with bullet points or section breaks.

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, 14 actions, and no output schema, the description covers the core conceptual model, including billing/auth fallbacks, install vs invoke distinction, and the prompt library. Missing parameter-level details for some actions and no mention of list/search return shapes, but the essential workflow is complete.

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 coverage is 0%, so the description carries the burden. It explains the action enum semantics and key parameters (action, mcp_id, tool_id, prompt_slug) through the described flow. However, it does not explain many other parameters (limit, query, tier_slug, immediate, conversation, cancel_reason), leaving the agent to infer their purpose.

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 is 'the official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It outlines specific capability requests and a core flow (search → describe → invoke), distinguishing it from sibling tools like connect, authenticate, and the garmin-specific tools.

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 when-to-use guidance is pervasive: 'prefer invoke for a single/occasional use', 'Use install only to make an MCP PERMANENT in the active toolkit', and alternatives are named ('list_tools lists what is callable right now', 'report_bug sends feedback', 'request_mcp asks us to build a NEW MCP').

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