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detect_regulatory_drift

Scan for regulation changes affecting DORA. Checks RegWatch + LawOracle + EU feeds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_idNoOptional

TDQS

B3.1/5.0
Behavior2/5

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

There are no annotations, so the description must disclose behavioral traits. It only lists data sources and implies a read-only scan, but does not state side effects, permissions, rate limits, or whether any state changes occur. The lack of output format and entity_id behavior further reduces 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 two concise sentences, each adding value: the first states the primary purpose, the second lists specific data sources. No unnecessary words or redundancy.

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?

Given no output schema and no annotations, the description leaves out critical context: what the tool returns, how the optional entity_id impacts results, and how this differs from other drift scans. The limited info is insufficient for an agent to fully understand the tool's behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter, entity_id, is described in the schema as 'Optional' with no additional context. The tool description does not mention this parameter at all, failing to explain how it affects the scan or when to provide it.

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 'Scan' and clearly identifies the resource: regulation changes affecting DORA. It also lists the specific data sources (RegWatch, LawOracle, EU feeds), which distinguishes it from sibling drift-detection tools like detect_cloud_drift and detect_control_drift.

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?

The description provides no explicit guidance on when to use this tool versus alternatives such as full_drift_scan or detect_control_drift. It does not mention exclusions or conditions, leaving the agent without clear decision criteria.

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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TDQS

C2.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with detection tools differentiated by drift type. Minor overlap exists between health_check and ping, as well as control_drift and evidence_drift sharing degraded controls, but descriptions provide enough context to avoid confusion.

Naming Consistency3/5

The naming pattern is mixed: detect_* tools consistently use verb_noun, but drift_history and drift_status follow noun_noun, and full_drift_scan is a compound noun. While readable, the inconsistency makes the set feel less cohesive.

Tool Count4/5

15 tools is slightly above average but justified by the broad scope of drift detection and management. Each tool earns its place, covering detection, viewing, configuration, and remediation without obvious redundancy.

Completeness4/5

The tool set covers the full drift lifecycle: detection (multiple types), full scan, history, status, configuration, manual marking/resolving, and automated remediation. Minor gaps like lacking a single-event detail view are not critical for core workflows.