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Baseline Safety Check

dcl_evaluate_safety

Assess agent responses for safety violations before action to prevent harmful outputs and support auditable AI operations.

Instructions

PRE-ACTION Baseline Safety Check ($0.01).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesIdentifier of the agent that produced the response.
responseYesThe agent or LLM response text to check for safety violations.
payment_idNoOptional payment identifier returned by a previous call when payment is required

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonYesHuman-readable explanation of why the verdict was reached.
tx_hashYesHash of this record in the tamper-evident audit chain.
verdictYesCOMMIT if the response passed policy checks, otherwise NO_COMMIT.
seal_textYesHuman-readable Leibniz Layer verification seal.
timestampYesUnix timestamp when this record was sealed.
confidenceYesConfidence score of the verdict, from 0.0 to 1.0.
drift_modeYesCurrent drift status: NORMAL, WARNING, ESCALATION, or BLOCK.
input_hashYesHash of the evaluated response (raw content is never stored).
verify_urlYesPublic URL to independently verify this seal.
chain_indexYesSequential index of this record in the audit chain.
drift_scoreYesZ-score measuring deviation of the recent commit rate from baseline.
policy_versionYesVersion of the policy that was applied.
Behavior1/5

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

The annotations are all false, providing no safety profile. The description adds no behavioral information about side effects, payment handling, or output structure. It fails to disclose anything beyond the cost.

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

Conciseness2/5

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

The description is extremely short, which is not the same as being concise. It omits essential information, making it under-specified rather than efficiently structured.

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

Completeness1/5

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

With an output schema and multiple sibling tools, the description should explain the tool's role and scope. It does not mention what 'baseline' means, how it differs from strict/fast/jailbreak checks, or what happens with the payment_id. This is inadequate for a paid evaluation tool.

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?

The input schema provides descriptions for all parameters (100% coverage), so the baseline is 3. The description doesn't add any parameter-specific context, but that's acceptable given schema coverage.

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

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is only 'PRE-ACTION Baseline Safety Check ($0.01).' It names the tool's category but doesn't use an explicit verb or explain what the check does. It doesn't distinguish from sibling evaluators like dcl_evaluate_fast or dcl_evaluate_strict.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool compared to the sibling evaluation tools. The 'PRE-ACTION' prefix vaguely hints at a temporal context, but no explicit scenarios or alternatives are given.

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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