DCL Trust Oracle — AI/LLM Output Audit (x402 MCP)

Strict Pre-Action Audit

dcl_evaluate_strict

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

Name	Required	Description	Default
`agent_id`	Yes	Identifier of the agent that produced the response.
`response`	Yes	The agent or LLM response text to audit.

Output Schema

TableJSON Schema

Name	Required	Description
`reason`	Yes	Human-readable explanation of why the verdict was reached.
`tx_hash`	Yes	Hash of this record in the tamper-evident audit chain.
`verdict`	Yes	COMMIT if the response passed policy checks, otherwise NO_COMMIT.
`seal_text`	Yes	Human-readable Leibniz Layer verification seal.
`timestamp`	Yes	Unix timestamp when this record was sealed.
`confidence`	Yes	Confidence score of the verdict, from 0.0 to 1.0.
`drift_mode`	Yes	Current drift status: NORMAL, WARNING, ESCALATION, or BLOCK.
`input_hash`	Yes	Hash of the evaluated response (raw content is never stored).
`verify_url`	Yes	Public URL to independently verify this seal.
`chain_index`	Yes	Sequential index of this record in the audit chain.
`drift_score`	Yes	Z-score measuring deviation of the recent commit rate from baseline.
`policy_version`	Yes	Version of the policy that was applied.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedAug 6, 2026

removedInput schema / properties / payment_id

Removed value: -{
-  "default": "",
-  "description": "Optional payment identifier returned by a previous call when payment is required",
-  "title": "Payment Id",
-  "type": "string"
-}

First observedAug 5, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations are all false, providing no behavioral cues, so the description carries the full burden. It discloses cost ($0.05), policy composition (union of three policies), threshold mechanics (0.85 vs 0.7), per-phrase confidence penalty (0.4), and exact verdict behavior (NO_COMMIT with reason listing all matches). There is no contradiction with annotations.

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 dense but every sentence earns its place: cost, policy scope, threshold, penalty, verdict behavior, and routing guidance. The most important differentiator (when to use it) is front-loaded and repeated in the final sentence, and no filler or redundant language appears.

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?

The description fully equips an agent to call this tool correctly: it explains the strict policy, the confidence mechanics, the output verdict, and the reasoning in 'reason'. Since an output schema exists and the closest sibling is explicitly distinguished, there is no missing decision-critical information.

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 'response' and 'agent_id' documented in the input schema. The description does not add new parameter-level meaning beyond what the schema already provides, so the baseline score of 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 uses a specific verb ('runs the response against') and resource ('broader, higher-bar strict policy'), then adds concrete mechanics: 8 forbidden phrases, 0.85 minimum-confidence threshold, and NO_COMMIT verdict. It clearly differentiates from sibling dcl_evaluate_fast by explicitly contrasting the stricter policy and threshold.

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 states when to use this tool: 'Use this instead of dcl_evaluate_fast when the cost of a false COMMIT is high' and gives a concrete example ('before an irreversible or high-stakes agent action'). It names the alternative and the condition, leaving no ambiguity.

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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