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check_message_safety

Analyze user messages to detect potential self-harm or criminal intent, enabling proactive safety interventions in chat platforms.

Instructions

Classify a message for self-harm or criminal intent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesThe user message to classify.
session_idNoOptional session identifier for trajectory tracking.mcp-default

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool classifies messages but doesn't describe how it behaves: it doesn't mention response format (though an output schema exists), accuracy or confidence levels, latency, rate limits, authentication needs, or whether it logs or stores data. For a safety-critical tool with zero annotation coverage, this is a significant gap in transparency.

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?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality ('Classify a message'), and every part of the sentence earns its place by specifying the classification criteria. There's zero waste or redundancy.

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

Completeness3/5

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

Given the tool's moderate complexity (safety classification with 2 parameters), no annotations, and an existing output schema, the description is minimally complete. It covers the basic purpose but lacks behavioral context (e.g., how classification works, error handling) and usage guidelines. The output schema mitigates the need to explain return values, but the description should do more to address safety implications and operational details.

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%, with both parameters ('message' and 'session_id') fully documented in the schema. The description adds no additional parameter semantics beyond what the schema provides (e.g., it doesn't explain message format constraints or session_id usage details). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to given the schema's completeness.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 a specific verb ('Classify') and resource ('a message'), specifying the classification criteria ('for self-harm or criminal intent'). It distinguishes itself from sibling tools like 'get_session_risk' and 'list_recent_escalations' by focusing on message classification rather than session-level or historical data analysis. However, it doesn't explicitly differentiate itself from potential alternatives beyond the provided siblings.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for use (e.g., real-time monitoring vs. batch processing), or comparisons with sibling tools like 'get_session_risk' (which might assess session-level risk) or 'list_recent_escalations' (which might show historical flagged messages). Usage is implied by the classification purpose but lacks explicit when/when-not instructions.

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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