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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, open-world), and the description adds value beyond them: cost ('Price: free'), error behavior ('returns isError ... not charged'), and data provenance from live recording. This is behavioral context an agent cannot get from the structured fields.

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?

Front-loaded with the core purpose, then data scope, then usage routing, then price and error semantics. Every sentence carries information (metrics, provenance, routing, cost, failure mode) with no filler.

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?

An output schema exists, so return values need not be explained, yet the description still lists the headline metrics. Combined with cost and error disclosure for a zero-param read tool, nothing an agent needs to invoke it correctly is missing.

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 tool takes no parameters, so there is nothing to document and the baseline is 4. The description correctly does not invent parameter semantics; it instead enumerates the output metrics, which is appropriate for a zero-arg tool.

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?

States a concrete verb and resource: a live market heartbeat with named metrics (trades/min, launches, graduations, graduation rate, hot tokens over 15 min). It also discloses the data source ('our own live recording of every pump.fun bonding-curve trade'), which distinguishes it from siblings like pump_history and pump_launches.

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 routing: 'Use it to decide whether the launch market is hot or dead before scanning individual tokens' and 'When to use: For the market right now; for trends over days use pump_history.' Names both the situation and the alternative, leaving nothing to inference.

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