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Scan a Terraform plan for security issues

scan_terraform_plan

Scan a Terraform plan JSON to identify security issues, receive severity ratings, suggested fixes, and corpus citations for remediation.

Instructions

Run the LangGraph scan agent against a Terraform plan JSON (output of terraform show -json). Returns structured findings with severity, suggested fixes and citations into the corpus. Defaults to LLM_PROVIDER=stub if no API key is configured.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
plan_jsonYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
findingsNo
llm_modelNo
embedding_modelNo
terraform_versionNo
resources_analyzedNo
plan_format_versionNo
Install Server

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It adds useful context: it invokes an LLM-dependent agent, defaults to a stub provider when no API key is configured, and returns structured findings. However, it does not disclose potential side effects, network usage, or what happens when the stub provider is used.

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?

Two sentences, front-loaded with the core action and input source, followed by return-value summary and configuration default. Every sentence adds distinct, useful information with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is a single-parameter operation with an output schema, so the description need not detail return values. It covers input provenance, output summary, and a key configuration default. The only minor gap is not elaborating on the stub-provider implication or environment expectations, but overall it is sufficient.

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

Parameters4/5

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

Schema coverage is 0%, but the description compensates by explaining that plan_json must be the output of 'terraform show -json'. Since there is only one parameter, this is sufficient to understand what to pass, despite the schema itself carrying no semantic description.

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 states a specific action ('Run the LangGraph scan agent') against a specific resource ('a Terraform plan JSON'), and clarifies the expected input format with the command that produces it. It clearly distinguishes the tool from its siblings, which search or list sources rather than scan.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when to use the tool: when you have a Terraform plan JSON and need security findings. It also provides the exact command to generate the input. However, it does not explicitly compare with the sibling tools or state when not to use it.

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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