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

Well beyond the readOnlyHint/openWorldHint=false annotations, it discloses the exact payload shape, the conditional honesty requirement about whether the first competitor check finished, the "at most three things to try" cap, and an optional path to import_win_loss or log_call_mentions with a requirement to state what will be read first. That is substantive operational context annotations cannot express.

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?

Purpose and trigger conditions are front-loaded in the opening sentence, and the turn-taking rule is placed where it blocks misuse. It runs long, with behavioral coaching ("greet them by company name once," "be honest") that borders on prompt engineering rather than tool documentation, but each sentence still carries usable direction.

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?

With no output schema, the description carries the return-value burden and does so fully, listing each returned element. For a zero-parameter entry-point tool in an 18-tool sibling set, everything needed to call it correctly — timing, one-shot nature, follow-up routing — is present.

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 zero parameters and the description confirms "no parameters," which matches the empty schema. There is no parameter meaning to add, so the baseline of 4 applies with no gaps to compensate for.

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?

"Onboarding entry point" is followed by a concrete enumeration of what the call returns (company name, first-check completion status, early findings, tailored prompts, single next step). The description also explicitly separates it from sibling tools (get_briefing, get_next_step), so an agent can identify it without inspecting any schema.

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 names precise triggering conditions: first call in a new conversation, user seems new, user asks what Ripplewatch can do, or asks what to do next. It also names the negative case and the alternatives: "Once the conversation is underway do not call it again: use get_briefing for updates and get_next_step for the next suggestion." This is a complete when/when-not/alternative mapping.

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