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

Annotations already declare the write/idempotent/non-destructive profile, so the description's real contribution is the validation and privacy behavior: unknown values are silently dropped, and personal data (names, emails, code, project names, free text) must never be sent. That is exactly the kind of consequence an agent needs before calling a write tool, though the response on success or partial drop is not stated.

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 purpose and the allowed tag set are front-loaded, then the safety constraint, then the routing note — a sensible order with little filler. The closing "Used by check_updates, not by recommend_tools" fragment is dense and slightly cryptic, but it is short enough not to hurt.

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 five-parameter, zero-required write tool with no output schema, the definition covers purpose, per-field values, validation behavior, and a privacy rule, which is close to what an agent needs. The residual holes are the value domains of `platforms`/`project_types` and the absence of any indication of what a successful call returns.

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?

With only 20% schema description coverage, the description carries most of the documentation burden and does so: it names all five parameters and supplies allowed values for `budget` (free|under_20|any) and `preferences` (nocode|code|open-source|free-tier), plus the meaning of `tools_in_use` as catalog ids. It stops short of specifying what valid `platforms` and `project_types` values look like.

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?

"Store the user's onboarding answers as non-sensitive tags" gives a concrete verb and resource, and the enumeration of the five tag groups makes the scope unambiguous. The one gap is the sibling `save_preferences`, which is nearly synonymous with this tool and is never distinguished from it.

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?

"Store the user's onboarding answers" implies the onboarding context for invocation, which is useful. However, "Used by check_updates, not by recommend_tools" describes which tools consume the stored data rather than when an agent should call this tool, and it gives no guidance on choosing between this and `save_preferences`.

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