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Jailbreak Detection Check

dcl_evaluate_jailbreak

Detect jailbreak attempts in LLM responses before action. Evaluates output against instructions to identify security breaches and ensure policy compliance.

Instructions

PRE-ACTION Instruction Adherence Check ($0.02). Detects jailbreak attempts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesIdentifier of the agent that produced the response.
responseYesThe agent or LLM response text to check for jailbreak attempts.
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.
Behavior3/5

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

Annotations provide minimal context (all hints false), so the description adds the cost ($0.02) and pre-action intent, which are useful. However, it does not disclose what happens after detection, whether it returns a score/flag, or other side effects 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.

Conciseness5/5

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

The description is extremely concise: two short sentences that front-load the purpose and cost. Every word contributes, with no filler or repetition.

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?

The tool has an output schema and well-described parameters, so the minimal description still conveys the core function. However, it lacks guidance on interpreting results or differentiating from the many sibling evaluation tools, making it only minimally complete.

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 coverage is 100% with clear parameter descriptions for response, agent_id, and payment_id. The description adds no additional parameter meaning, but the schema already explains them well, so baseline 3 is appropriate.

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 detects jailbreak attempts in a response, using the specific verb 'detects' and resource 'jailbreak attempts'. This distinguishes it from sibling evaluation tools like dcl_evaluate_secrets or dcl_evaluate_safety, which target different risks.

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

Usage Guidelines3/5

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

The description implies usage as a pre-action check via 'PRE-ACTION' and mentions a cost, but it does not explicitly say when to use this tool versus alternatives like dcl_evaluate_fast or dcl_evaluate_safety. No exclusions or alternative recommendations are given, so the guidance is only implied.

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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