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Подтверждение пароля

confirm_password

Verifies the account password entered via a terminal login script, keeping credentials private from the AI agent. Invoke when banking requests a password on first login to a new device.

Instructions

НЕ вызывай напрямую из чата: пароль аккаунта не должен проходить через агента. Этот тул существует для login_cli.py, который читает пароль из терминала, невидимого модели. Если банк просит password (первый логин на новом устройстве) — попроси пользователя запустить login_cli.py.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
passwordYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description goes beyond the annotations by disclosing a critical security-sensitive behavior: the password is read from a terminal invisible to the model and must not be handled by the agent. This prevents a misuse that annotations alone could not express. It also clarifies the CLI's role and the intended execution context.

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?

Three short, information-dense sentences are placed in logical order: prohibition first, reasoning second, actionable alternative third. Every sentence earns its place and there is no filler or redundant schema repetition.

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?

For a one-parameter security-sensitive tool, the description is complete. It tells the agent why the tool exists, how the password is handled, when the bank may request it, and exactly what action the agent should take. The existing output schema covers any required return-value detail, so nothing essential is missing.

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 only provides a 'password' title with no description, but the tool description adds essential semantic context: this is the account password, it must not be transmitted through the agent, and for the CLI flow it is read directly from the terminal. It does not specify format constraints, but the security-critical meaning of the parameter is clearly conveyed.

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 what the tool is for: password confirmation for first login on a new device, but only for the login_cli.py flow. It also explicitly differentiates it from a chat-accessible tool by warning 'НЕ вызывай напрямую из чата'. The agent knows the tool's role and how it differs from a normal login/confirmation flow.

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

Usage Guidelines5/5

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

The description gives explicit when-to-use and when-not-to-use guidance. It says the agent must never call it from chat, explains the password must not pass through the agent, and tells the agent exactly what to do instead: ask the user to run login_cli.py when the bank requests a password on a new-device first login.

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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