detect_evidence_drift
Find stale assessments + expired evidence + degraded controls.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | No |
driftoracle
TDQS
C2.7/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description bears full responsibility for behavioral disclosure. However, it only lists the items being found and says nothing about whether the tool is read-only, what it returns, if it has side effects, or if any permissions are required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but under-specified. It is not structured to convey necessary context about usage or parameters. While it avoids verbosity, it lacks completeness and could benefit from additional sentences.
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?
With no output schema and minimal parameter documentation, the description needs to supply more context. It only hints at purpose and lacks prerequisites, return behavior, and differentiation from the many sibling drift detection tools, making it insufficient for an agent to confidently invoke the tool.
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 only parameter, entity_id, is completely unexplained. The schema provides just a string type, and the description does not mention it at all (schema coverage 0%). The agent cannot infer what entity_id refers to or how it filters the results.
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 'Find' and names three distinct resources ('stale assessments', 'expired evidence', 'degraded controls'), which clearly indicates the tool's focus on evidence drift. The mention of 'evidence' distinguishes it from sibling drift detection tools like detect_control_drift or 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?
No guidance is provided on when to use this tool versus alternatives. The description only states what it finds, but does not mention prerequisites, exclusions, or scenarios where another drift detection tool might be more appropriate.
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.