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

The annotations already mark it read-only and non-destructive, and the description adds substantial behavioral context: private Telegram corpus, no purchasable alternative data source, no message text returned, room-count only, and the presence of corpus_through in every response. It also discloses the ~70/30 corpus-wide split as an important data trait.

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 information-dense and front-loads the core output, then explains sourcing, privacy, caveats, and cost. It loses a point for redundancy: 'Costs $0.03 USDC on Base' and '(paid $0.03 — see instructions)' say basically the same thing.

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?

Even without an output schema, the description explains what the agent will receive: first Telegram timestamp, first X timestamp, lead in minutes, room count, and corpus_through. The unit for lead is specified, privacy limitations are clear, and this is enough to call the tool correctly for the single required parameter.

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 input schema already fully documents the one token parameter as a Robinhood Chain token address, so the description does not need to add much. The description reinforces that the outcome is per-token and requires a single Robinhood Chain token, but it adds no new syntactic or semantic detail beyond the schema.

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 names a specific verb and resource: comparing the first Telegram timestamp, first X timestamp, and lead in minutes for a Robinhood Chain token. This clearly distinguishes it from sibling tools centered on mentions, tokens, or callers.

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?

The description gives clear interpretative guidance: use the per-token number, not the corpus-wide average, because the distribution is bimodal. It also clarifies limits (source rooms never identified, no message text) and cost, though it does not explicitly name sibling alternatives or state when not to use the tool.

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