delete_my_accountErase the account and everything in it: profile, CV files, matches, applications, answers, keys. Irreversible. Requires confirm_email equal to the account's address.
| Name | Required | Description | Default |
|---|---|---|---|
| confirm_email | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already include destructiveHint=true, and the description adds important behavioral detail: the operation is irreversible, it destroys specific categories of data, and it requires confirm_email to match the account address. There is no contradiction with the annotations.
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 action and scope. The data enumeration is necessary for transparency and the confirmation requirement is stated directly. No filler or redundancy.
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 one parameter, destructive annotations, and no output schema, the description covers action, scope, irreversibility, and the prerequisite for invocation. Nothing needed to call the tool correctly 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?
The schema only defines confirm_email with an email format; the description supplies the essential semantic requirement that it must equal the account's email address. This fully compensates for the 0% schema description coverage.
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 uses a specific verb ('Erase') and precisely identifies the resource ('the account') and everything it contains. The enumerated data types make it easy to distinguish from sibling tools like delete_saved_answer or cancel_subscription.
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 makes the context clear: this is for permanent, whole-account deletion, not a partial operation. It does not explicitly name alternatives such as cancel_subscription or export_my_data, but the scope is explicit enough for an agent to infer when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tool purposes are generally distinct and well-described, but a few clusters overlap in function: answer_screening_question vs save_answer both write to the answer book, get_my_profile vs get_account both report plan status, and the CV preview/sent-CV/base-CV tools could be confused. The detailed descriptions mitigate most misselection, so this is only a minor issue.
The set almost uniformly uses snake_case verb_noun names like list_, get_, update_, create_, delete_, and start_/stop_. Minor deviations such as login, describe_what_i_want, and the get_my_* vs list_* alternation prevent a perfect score, but the overall pattern is predictable and readable.
49 tools is far above the 25+ threshold and will burden agent tool selection even though many are legitimate single-purpose operations. Several groups could be consolidated—billing links, API-key management, and the CV PDF family—without hurting clarity.
The surface covers the full lifecycle: account creation/auth, profile and CV, targeting, matching, apply runs, screening answers, tracking, billing, export, and deletion. Minor gaps remain, such as no application-level detail/withdrawal endpoint and no direct way to save a parsed CV without re-uploading, but agents can work around them.