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CSOAI-ORG

Patient Safety AI MCP

generate_safety_alert

Generate structured clinical safety alerts by analyzing drug and alert type inputs against established safety frameworks. Supports interaction, allergy, dosage, and contraindication alerts.

Instructions

Create a formatted clinical safety alert. Alert types: interaction, allergy, dosage, contraindication.

Behavior: This tool generates structured output without modifying external systems. Output is deterministic for identical inputs. No side effects. Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: drug (str): The drug to analyze or process. alert_type (str): The alert type to analyze or process. severity (str): The severity to analyze or process. patient_id (str): The patient id to analyze or process. details (str): The details to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drugYes
api_keyNo
detailsNo
severityNomoderate
alert_typeYes
patient_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Despite no annotations, the description extensively covers side effects (read-only, no side effects), authentication (no auth for basic, API key for pro), rate limits (free: 10/day, pro: unlimited), error handling (structured errors), idempotency, and data privacy. This fully compensates for missing annotations.

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?

Well-organized with sections, but somewhat verbose as behavioral transparency details are repeated under both 'Behavior:' and 'Behavioral Transparency:'. Could be more concise without losing clarity.

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?

Covers behavior, usage, transparency thoroughly. Has output schema, so return format not needed. However, lacks integration context with sibling tools (e.g., whether this tool is meant to be used after specific checks). Still, fairly complete for a generation tool.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must add meaning. However, the 'Args' section only provides generic phrases like 'The drug to analyze or process' for each parameter, adding little beyond the parameter name. Missing specifics like valid alert types or severity levels.

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 creates a formatted clinical safety alert and lists specific alert types (interaction, allergy, dosage, contraindication). It distinguishes from sibling tools like check_allergy_conflicts and check_drug_interactions by focusing on generating a formatted alert rather than just checking.

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?

Explicit 'When to use' and 'When NOT to use' sections provide clear guidance. It recommends use for structured analysis/classification and warns against real-time production use without human review. This helps an AI agent decide when to invoke this tool.

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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