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

Annotations already establish readOnly, idempotent, non-destructive behavior, and the description adds valuable context: data is refreshed hourly and the metrics are retrospective ('Past facts, not a forecast'). It doesn't state rate limits, caching, or latency, but for a read-only aggregate tool this is strong.

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-loads the core definition with a specific refresh cadence, then lists metrics compactly, then gives the usage clause last. It's dense but each clause carries information; it could be split for readability but nothing is waste.

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 zero-parameter read-only tool with no output schema, the description fully covers what the agent will receive and when to call it. The only missing piece is any note on freshness guarantees beyond 'hourly' or failure modes, which is minor.

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?

There are zero parameters, so baseline is 4. No parameter semantics are needed; the description instead spends its space describing the return content.

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 specific resource (pump.fun weather) and enumerates exactly what it returns: launches/hour, pre-prepared share, dumping share, migrations, winning positions, entry-speed profitability, serial teams. It's clearly distinguishable from siblings like simulate_bot or check_wallet, which concern a bot or a wallet rather than market state.

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?

Explicitly says when to use it: 'before tuning a bot' and 'when someone asks what is happening on pump.fun now.' It also clarifies the boundary 'Past facts, not a forecast,' which tells the agent this is retrospective data, not predictive.

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