get_remediationCompute a remediation plan for a threat/finding WITHOUT applying it (mode=dry_run). Runs the same governed engine as apply_remediation, including the patent gates, and returns the proposed steps.
| Name | Required | Description | Default |
|---|---|---|---|
| rule_id | Yes | Policy/rule id (e.g. AWS_S3_PUBLIC_ACCESS) | |
| threat_id | Yes | Threat id/code to remediate | |
| resource_context | No | provider/resource_id/region/account_id/metadata |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description adds key behavioral traits: it does NOT apply the plan, runs the same engine as apply_remediation, includes patent gates, and returns proposed steps. This adds significant value beyond the structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The purpose is front-loaded, and each sentence adds essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the three parameters (one nested) and no output schema, the description explains what the tool does and returns, but does not specify the output format or structure of the proposed steps. It is adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all three parameters with descriptions. The description does not add further meaning beyond the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it computes a remediation plan without applying it, using a dry run mode. The verb 'compute' and resource 'remediation plan' are specific, and it explicitly distinguishes from the sibling 'apply_remediation'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies when to use (to get guidance without applying) and implies the alternative 'apply_remediation'. It mentions running the same engine including patent gates, providing useful context. However, it does not explicitly state when not to use or list other alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes (e.g., apply vs. get remediation, scan vs. status). A few pairs like get_insights and get_diagram_summary overlap slightly in metrics but descriptions clarify differences. No major ambiguity.
Predominantly verb_noun pattern (apply_, get_, generate_). However, code_review_scan and compliance_scan are noun phrases without a leading verb, and compliance_status is noun_noun, introducing minor inconsistency.
15 tools is at the upper end of typical but still reasonable for a security platform covering scanning, remediation, threat modeling, billing, and reporting. Each tool serves a clear function; no obvious bloat.
Covers core workflows: code/cloud/compliance scanning, threat modeling, remediation (dry-run and apply), traceability, insights. Minor gaps like missing scan listing or account management, but these align with the platform's assessment focus.