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record_oversight

Record human decisions (approve, refuse, override, stop, review) in the action ledger for auditability and compliance with EU AI Act Art. 14 and GDPR Art. 22.

Instructions

Record a HUMAN decision about the agent's work in the action ledger: approve, refuse, override, stop or review (EU AI Act Art. 14, GDPR Art. 22). actor is the person or role who decided and is required. refers_to is the seq of the action it concerns and must exist. decision is what the human substituted, stored as a digest.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorYes
eventYes
reasonNo
decisionNo
refers_toNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.39.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does convey that the tool writes to an action ledger and that decision is persisted as a digest, and it surfaces validation constraints like refers_to must exist. However, it does not disclose whether entry is append-only, whether anything can be overwritten, or what happens on validation failure—important behaviors for an audit-related write tool.

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 compact, front-loads the core purpose, and uses backtick-delimited parameter explanations that are easy to scan. The legal citations add context but are not directly operational. It earns a 4 rather than 5 because some required parameter guidance is missing and the legal references, while useful, are secondary to invocation.

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

Completeness2/5

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

For a 5-parameter tool with no annotations and no output schema, the description is not complete enough. It covers the core purpose and several constraints but omits the required `event` field, leaves `reason` unexplained, and does not describe expected return or error behavior. An agent could still mis-invoke this tool because a required parameter's semantics are unclear.

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 0%, so the description must supply meaning. It does well for actor, refers_to, and decision, explaining identity, linkage, and digest storage. However, it never explains the required `event` parameter or the optional `reason` parameter, and the relationship between `event` and `decision` is left ambiguous—a significant gap given event is required.

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 states a specific verb and resource: 'Record a HUMAN decision about the agent's work in the action ledger.' It enumerates the decision kinds (approve, refuse, override, stop, review) and the legal context, making the tool's purpose unmistakable. It also differentiates this from sibling read/report tools by emphasizing 'HUMAN decision' and the action ledger.

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 gives clear conditions for correct use: actor is required, refers_to must reference an existing action, and decision is stored as a digest. However, it does not explicitly state when to prefer this tool over siblings like record_decision or record_incident, nor does it provide when-not-to-use exclusions. The legal references imply an oversight/regulatory use case, but the guidance is incomplete.

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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