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Deep Forensic Audit Decode

dcl_audit_decode_deep
Read-onlyIdempotent

Perform deep forensic audit of a transaction to retrieve extended audit records with drift context and full chain integrity verification, enabling tamper-evident post-action review.

Instructions

POST-ACTION Deep Forensic Audit ($0.50). Extended output with drift_context and full chain integrity verification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tx_hashYesTransaction hash of the audit chain record to retrieve.
payment_idNoOptional payment identifier returned by a previous call when payment is required

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoSet if tx_hash was not found; other fields are omitted.
reasonNoExplanation recorded for the verdict.
tx_hashNoHash of the audit chain record.
verdictNoCOMMIT or NO_COMMIT.
agent_idNoIdentifier of the agent tied to this record.
prev_hashNoHash of the preceding record in the chain.
seal_textNoHuman-readable Leibniz Layer verification seal.
task_typeNoTask type tag recorded with this entry.
timestampNoUnix timestamp when the record was created.
confidenceNoConfidence score recorded for the verdict.
verify_urlNoPublic URL to independently verify this seal.
chain_indexNoSequential index of the record in the chain.
drift_contextNoExtended forensic metadata captured at evaluation time.
tamper_reasonNoWhy chain_integrity is False — a broken prev_hash link or an edited row whose stored tx_hash no longer matches its recomputed content hash.
chain_integrityNoTrue if the full chain verifies as intact.
tampered_at_indexNoIndex where chain integrity broke, if any tampering was detected.
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the description adds value by disclosing the $0.50 cost, extended output fields, and full chain integrity verification. This gives the agent useful operational context beyond the structured safety hints.

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

Conciseness4/5

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

The description is concise, front-loaded with the tool's purpose, and includes cost and key output features in one sentence. It avoids redundancy, though it sacrifices some contextual guidance that could make it more complete.

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 presence of an output schema and complete annotations, the description provides additional useful context like cost and extended verification. However, it lacks a comparison with the dcl_audit_decode sibling and doesn't explain what drift_context is, leaving some contextual gaps for an agent deciding between similar tools.

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 both parameters already described clearly. The description adds no additional parameter-level semantics; it only mentions cost and output characteristics. Since the schema handles the parameter meaning, a baseline of 3 is appropriate.

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 identifies this as a deep forensic audit decode for post-action review, with extended output including drift_context and full chain integrity verification. It distinguishes itself from the sibling dcl_audit_decode by the word 'Deep' and the mention of extended output, though it doesn't explicitly contrast the two.

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?

No explicit guidance is provided for when to use this tool versus alternatives like dcl_audit_decode. The phrase 'POST-ACTION' implies a usage context, but there is no clear statement of when to choose this deep variant or any exclusions.

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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