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Strict Pre-Action Audit

dcl_evaluate_strict

Run a strict high-stakes pre-action audit on LLM responses, catching jailbreak and safety-adjacent phrasing with a higher confidence threshold. Returns NO_COMMIT with reasons if any match.

Instructions

STRICT Pre-Action Audit ($0.05). Runs the response against a broader, higher-bar "strict" policy: the union of all forbidden phrases from the default, anti-jailbreak, and safety policies (8 phrases total), with a 0.85 minimum-confidence threshold instead of the default policy's 0.7. Each matched phrase costs 0.4 confidence; if confidence falls below 0.85, or any phrase matches, the verdict is NO_COMMIT with reason listing every match found. Use this instead of dcl_evaluate_fast when the cost of a false COMMIT is high — e.g. before an irreversible or high-stakes agent action — since it catches jailbreak- and safety-adjacent phrasing that the plain default policy would miss.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesIdentifier of the agent that produced the response.
responseYesThe agent or LLM response text to audit.
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.
Behavior5/5

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

The description discloses detailed behavior beyond the neutral annotations: the $0.05 cost, the union of forbidden phrases from three policies, the 0.85 confidence threshold, the 0.4 confidence deduction per matched phrase, and the exact NO_COMMIT condition. It also mentions the `reason` field listing matches, giving full behavioral 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 concise and every sentence adds value: cost, policy details, thresholds, verdict logic, and usage guidance. It is front-loaded with the tool's name and cost, and contains no filler or repetition.

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

Completeness5/5

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

Given the output schema exists, the description fully covers the tool's behavior, including the verdict conditions and the `reason` field. It provides enough context for an agent to invoke the tool correctly and interpret likely results, without needing to infer missing 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?

The schema descriptions cover all three parameters (response, agent_id, payment_id) with 100% coverage, so the schema already provides the needed meaning. The description does not add parameter-specific details beyond what the schema states, matching the baseline 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 function: it runs an audit of a response against a broader strict policy, specifying exact thresholds (0.85 vs 0.7) and the verdict outcome. It explicitly differentiates from sibling tool dcl_evaluate_fast, making the purpose unambiguous.

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?

The description explicitly tells when to use this tool instead of dcl_evaluate_fast: when the cost of a false COMMIT is high (e.g., irreversible or high-stakes actions). It provides a clear alternative and a rationale, fulfilling the when/when-not guidance.

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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