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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds useful context that the check is based on ELC's actual launch playbook and returns a verdict plus open gaps, so an agent knows what kind of answer to expect and that no mutation occurs.

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?

Two sentences, front-loaded with the core question and outcome, with the provenance detail kept to the second sentence. The city list and 'actually' add credibility but are non-essential for tool invocation, so it is slightly above average but not maximally tight.

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?

Given the optional answers object, read-only annotations, and presence of an output schema, the description gives enough to understand what to pass and what to expect. It explains the five-question flow, the verdict-plus-gaps result, and where the check comes from; no critical usage context 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?

Schema description coverage is 100%, so the baseline is 3; the schema already documents answers as responses to the five questions and context as an analytics string. The description only adds the count of questions and the playbook provenance, not per-parameter semantics.

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 the tool answers a specific question — whether to start an engineering-leadership meetup in a given city — and describes a five-question readiness check returning a verdict and gaps. This clearly distinguishes it from sibling tools like assess_speaker_readiness and evaluate_meetup_topic.

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 question phrasing ('should I start...') makes the invocation context obvious, and the readiness-check framing implies it is for city-launch decisions rather than speaker or topic assessment. It does not explicitly name alternatives or exclusion conditions, so it earns a 4 rather than a 5.

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