trigger_remediation
Self-healing: sync all data, run escalation, collect evidence, auto-resolve drift events.
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?
With no annotations, the description carries the full burden of behavioral disclosure. It lists actions but omits side effects, permissions, reversibility, or the scope of 'all data,' which is concerning for a mutation-capable 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 a single concise sentence with no filler, front-loading the core purpose. However, it is cryptic and misses critical context, so while concise, it is not fully self-sufficient.
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 the lack of annotations, output schema, and schema descriptions, the description must provide substantial context. It lists several workflow steps but fails to explain return values, failure modes, or the scope of 'all data,' leaving the agent underinformed for a complex remediation tool.
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 single parameter entity_id is not mentioned in the description, and schema coverage is 0%. The parameter name is self-explanatory to some degree, but the description adds no value regarding expected values, optionality, or how it affects the remediation workflow.
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 the tool as a self-healing remediation action, listing concrete steps (sync all data, run escalation, collect evidence, auto-resolve drift). It distinguishes itself from sibling 'resolve_drift' by emphasizing automation, though it doesn't explicitly name that alternative.
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 given on when to use this tool versus alternatives like resolve_drift or mark_drift. The 'self-healing' label implies automated use, but there are no explicit conditions, prerequisites, or 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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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.