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request_approval

Submit AI agent actions for biometric human approval via Face ID. Returns request ID and status, with auto-approval or denial rules for varying risk levels.

Instructions

Request human approval for an AI agent action via Face ID.

Submit any action (email, purchase, booking, contract, data access, social post, system change) for biometric verification by the authorized human. Returns immediately with request ID and initial status — the action may be auto-approved/denied by rules, or pending human review.

Action types: communication, purchase, scheduling, legal, data_access, social, system Risk levels: low, medium, high, critical

Example: Request approval to send an email action_type: "communication" title: "Send quarterly report to john@company.com" risk_level: "low"

Example: Request approval for a $500 purchase action_type: "purchase" title: "Purchase cloud hosting credits" amount: 500.00 risk_level: "medium"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
action_typeYesCategory of the action
titleYesShort description shown to the approver
descriptionNoDetailed description of the action (optional)
risk_levelNoRisk classification (affects UI urgency and rule evaluation)medium
amountNoDollar amount, if applicable (e.g., purchases)
recipientNoWho receives the action (email address, merchant name, etc.)
reversibleNoWhether the action can be undone
metadataNoArbitrary key-value pairs for audit trail
expires_in_secondsNoSeconds until the request auto-expires (default: 5 minutes)
callback_urlNoHTTPS URL to receive webhook when approval status changes (optional)
Behavior4/5

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

The description discloses key behaviors: returns immediately with request ID and status, can be auto-approved/denied or pending, and uses biometric verification. It does not contradict any annotations (none provided). However, it could add more detail about potential failures or cancellation behaviors.

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

Conciseness4/5

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

The description is well-structured: a concise summary, followed by lists of action types and risk levels, and two illustrative examples. It is appropriately sized for a complex tool with 10 parameters, though slightly longer than necessary. Every section adds value.

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?

Given the 10 parameters, 100% schema coverage, and no output schema, the description sufficiently covers the tool's purpose, parameters, and behavior. It explains return values (request ID and status) and includes examples. Additional details about output format or error handling would increase completeness.

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 already has 100% parameter description coverage, so the baseline is 3. The tool description adds value beyond the schema by providing examples, explaining how risk_level affects UI urgency, and showing typical use cases for amount and action_type. This justifies a 4.

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's function: requesting human approval for AI actions via Face ID. It lists specific action types and risk levels, and provides examples that illustrate usage for different scenarios. The sibling tools include check_approval and get_approval_history, which are distinct, so the tool stands out clearly.

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 explains when to use the tool (when human approval is needed) but does not explicitly state when not to use it or compare it with alternatives like check_approval or wait_for_approval. The examples give good context, but explicit guidance on avoiding this tool for non-approval actions would improve clarity.

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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