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submit_login_code

Complete a sign-in started by login, using the 'code' value the user copied from the browser address bar. On success the user can place orders from that restaurant.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesThe code value copied from the redirect URL after signing in.
labelNoOptional label for this account, e.g. 'work' or 'personal'. Defaults to the email address on the account.
clientIdNoclientId of the restaurant being signed in to. Omit if only one sign-in is in progress.

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does state the main effect (completes sign-in, enables order placement) and the input source (browser address bar), but it does not mention potential side effects, session state changes, or error conditions such as invalid or expired codes.

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?

Two sentences, no filler. The description front-loads the purpose, then states the input source and the success outcome. Every sentence contributes useful information.

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

Completeness4/5

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

For a simple tool with three parameters and schema coverage of 100%, the description provides the key workflow context: it follows login, uses a browser-copied code, and enables ordering from that restaurant. It does not describe the return value or all possible failure modes, but these are somewhat outside the core description burden given the simple schema.

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

Parameters3/5

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 all three parameters. The description reinforces the meaning of 'code' but adds no additional semantics for 'label' or 'clientId' beyond what the schema provides.

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?

The description clearly states the tool completes a sign-in started by login, using a code from the browser address bar. It also distinguishes this from the login step by naming 'login' as the starting point, and clarifies the outcome (ability to place orders from that restaurant).

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?

The description gives clear context: use this after login has started and the user has copied a code from the browser address bar. It implicitly contrasts with login by saying 'started by login,' but it does not explicitly list when-not-to-use or mention alternatives like switch_account.

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

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct action and resource: order status vs. order staging vs. order placement, vendor discovery vs. menu retrieval, and login initiation vs. code submission. There is no overlap or ambiguity; even sequential tools like prepare_order and place_order are clearly separated by their purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with lowercase and underscores (e.g., check_order, list_vendors, prepare_order). Even the login and logout tools fit the pattern as single verbs, and there is no mixing of conventions.

Tool Count5/5

With 10 tools, the surface is well-scoped for a restaurant ordering domain. It covers discovery, menu browsing, account management, login flow, order staging, placement, and status checking without feeling bloated or too thin.

Completeness4/5

The core ordering lifecycle is covered end-to-end (vendor -> menu -> login -> prepare -> place -> check). The only noticeable gaps are the absence of an explicit address-saving tool (though referenced in the login description) and no order cancellation or update capability, though these may be out of scope for typical ordering workflows.

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