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ODEI MCP Server

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by odei-ai

odei_guardrail_check

Validate agent actions against safety guardrails before execution. Checks financial transactions, communications, and scheduling against 7 layers of constraints including financial limits, time restrictions, and value alignment.

Instructions

Validate an agent action against ODEI's constitutional guardrails. Returns APPROVED, DENIED, or NEEDS_REVIEW with reasoning. Use this before executing any action that could affect finances, reputation, health, or relationships. The guardrail system checks against 7 layers of safety constraints including financial limits, time-of-day restrictions, and value alignment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesThe action to validate (e.g., "Transfer 5 ETH to external wallet", "Post tweet about token price", "Schedule meeting at 11pm")
contextNoAdditional context about the action — who initiated it, why, what system it affects
domainNoWhich domain layer this action operates in
severityNoSelf-assessed severity of the action (helps calibrate the check)
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it describes the return values (APPROVED, DENIED, NEEDS_REVIEW with reasoning), mentions the 7-layer safety constraint system, and specifies domains of application. It doesn't cover rate limits or error handling, but provides substantial operational 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?

Two sentences that are front-loaded with core functionality, followed by usage guidance. Every sentence earns its place by providing essential information without redundancy or fluff.

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 validation tool with no annotations and no output schema, the description does well by explaining return values and behavioral context. It could improve by detailing error cases or system limitations, but covers the core functionality adequately given the complexity.

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 parameters thoroughly. The description doesn't add any additional parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for high schema coverage.

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 purpose with specific verbs ('validate an agent action against ODEI's constitutional guardrails') and resources (guardrails). It distinguishes from siblings by focusing on safety validation rather than auditing, querying, or signaling.

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?

Explicitly states when to use ('before executing any action that could affect finances, reputation, health, or relationships') and provides clear context about appropriate scenarios. No alternatives are mentioned, but the guidance is comprehensive and actionable.

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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