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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered and the description correctly does not repeat it. It adds nothing beyond that, however: the stateful conversation_id handshake, the prohibition on parallel calls before the first response, and the fact that this is a meta/discovery call with a non-data payload are all disclosed only in the schema, not the description.

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?

A single front-loaded sentence with an em-dash clause carrying the only caveat that matters. Nothing is wasted and the trigger precedes the qualifier.

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?

There is no output schema, so the description carries the burden of explaining what a call yields, and it does not: an agent cannot tell whether it receives tool definitions, a yes/no answer, or instructions to re-query. The rich schema descriptions recover the procedural half of that gap, but the outcome of the call remains unstated for a three-parameter, open-world tool.

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% and the parameter descriptions are unusually rich, including a full explanation of the conversation_id lifecycle and a no-guessing rule for llm_model. The description adds no parameter-level meaning at all, so the baseline 3 applies.

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 states a specific action ('Check for additional tools') and its trigger ('whenever your task might benefit from specialized capabilities'), which is enough to separate it from every sibling, all of which are concrete Instagram/TikTok/YouTube data tools. It stops short of saying what actually comes back (a set of newly available tool definitions), so the agent knows the intent but not the mechanism.

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?

It gives explicit call-condition guidance, including a deliberate anti-hesitation clause ('even if existing tools could work as a fallback'), which is the key decision an agent faces with a discovery tool. It omits any when-NOT guidance (e.g., don't call repeatedly once tools are loaded), which is the main failure mode for a tool like this.

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