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keywordise

Create a Keywordise account

create_account

Register a new Keywordise account from the terminal and receive an API key for it. Requires accept_terms=true: the person accepts the Terms and Privacy Policy (https://keywordise.com/terms) and authorises Keywordise to apply for jobs on their behalf. A confirmation email is sent; applying opens once the address is confirmed. Trial: 7 days and 27 applications, then $49/month.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYes
passwordYes
accept_termsYes

TDQS

A4.7/5.0
Behavior5/5

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

Discloses major side effects beyond annotations: it authorises Keywordise to apply for jobs on the user's behalf, sends a confirmation email, gates applying on address verification, and sets a trial quota (7 days/27 applications, then $49/month). Annotations are all false and convey none of this, so the description carries the behavioral burden well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four tight sentences, with the core purpose in the first sentence and supporting prerequisites/effects in the rest. There is no redundant filler or repetition of schema fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers what the tool does, the key precondition, the post-conditions (API key, confirmation email, activation rule), and cost/quota. Since there is no output schema, the return value (an API key) is explicitly mentioned, making this complete enough to call correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero parameter descriptions, but the description compensates by explaining accept_terms in depth: what true means legally and the job-application authorisation it grants. Email and password semantics remain self-evident from their types/constraints, so the critical non-obvious parameter is covered.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States exactly what it does: 'Register a new Keywordise account from the terminal and receive an API key for it.' The verb+resource is specific and the 'new' framing differentiates it from sibling operations like login or create_api_key, even without naming them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clearly frames when to use it: to register a brand-new account, including the terminal context and the accept_terms prerequisite. It does not explicitly point to login or create_api_key as alternatives for existing users, so when-not guidance is absent.

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

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TDQS

A3.6/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness4/5

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.

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