detect_control_drift
Controls that degraded from GREEN to YELLOW/RED.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | No |
driftoracle
TDQS
D1.9/5.0
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 states a condition ('degraded from GREEN to YELLOW/RED') and does not mention whether the tool is read-only, what output it returns, or any side effects. This is insufficient for a tool despite the implied 'detect' in the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise, but it is under-specified rather than effectively structured. It omits essential details about the tool's function and parameters, so the brevity reduces clarity.
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 tool with one parameter, no annotations, and no output schema, the description is incomplete. It does not explain the return value, the meaning of entity_id, or how this relates to other drift tools. The description provides only a minimal definition of drift, leaving major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter (entity_id) with no description, and schema description coverage is 0%. The description does not mention entity_id at all, so the agent has no guidance on what this parameter represents or whether it is optional. The description fails to compensate for the sparse schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a noun phrase with no verb, stating what the tool identifies ('Controls that degraded from GREEN to YELLOW/RED') rather than what it does. It adds some specificity about the drift criteria, but fails to clearly state an action, making it vague and not properly differentiated from sibling tools like detect_cloud_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 offers no guidance on when to use this tool versus alternatives such as detect_cloud_drift or detect_enterprise_drift. No context or exclusions are provided, leaving the agent to infer usage.
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.