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

Goes well beyond the annotations by disclosing real side effects: Moda saves name, email and Facebook profile before releasing a code, sends email (and optionally phone/SMS), and the private-group code is never returned while the moda-ai code is. It also spells out the consent/terms and privacy-policy agreement that the call implies, plus the opt-out language. This is exactly the kind of consequence disclosure the sparse annotations (destructiveHint=false, idempotentHint=false) do not provide.

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 purpose and then branches cleanly by code_type, with the consent and return information grouped at the end. The legal URLs and SMS opt-out boilerplate are slightly heavy for a tool description, but each block carries genuine behavioral information rather than 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?

With no output schema, the description correctly covers return values: a JSON result indicating where the code went, the code itself for moda-ai, or the failure reason. For a 7-parameter tool that writes PII and triggers email/SMS, it also covers consent, side effects, and conditional parameter relevance, leaving nothing material an agent needs before calling.

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 schema already documents every parameter, including the group enum and the code_type enum; baseline would be 3. The description adds usable conditional meaning, noting that group and phone are only relevant for private-group and that code_type determines whether a code is emailed versus returned. That conditional framing is modest added value rather than new syntax or format detail.

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 verb and resource ("Gets a person their Moda join code") and pins it to a recognizable real-world equivalent (the form at modacommunities.com/join-code). It further splits the purpose by code_type (private-group vs moda-ai), which is genuinely clarifying. It does not differentiate itself from siblings such as find_moda_groups or check_facebook_group_link, so it stops short of a 5.

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?

Gives a concrete usage trigger: "Most Moda Facebook groups are private, and their join question asks for this code," which tells an agent when to reach for this tool. It also states the required precondition (name, email, facebook_profile, code_type, agrees_to_terms) that governs invocation. It never names an alternative tool or an explicit "do not use when," so it lands at a clear-but-not-exhaustive 4.

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