In 2026, Atlas helps Terraform HCL developers produce accurate README documentation for modules by directly reading source code, ensuring the documentation reflects current behavior rather than outdated intentions. It integrates with your existing `terraform init` and `terraform fmt` workflows to provide traceable, up-to-date module descriptions, addressing the critical need to document what the code actually does today, not what it was supposed to do a year ago. Atlas leverages its understanding of Terraform HCL's structure to enumerate resources, variables, and outputs, then verifies code samples with `bash` for unparalleled accuracy.
How Atlas generates Terraform HCL module READMEs from code
Atlas generates Terraform HCL module READMEs by directly inspecting your `.tf` files and `.terraform.lock.hcl` in 2026, ensuring documentation reflects the actual state of your infrastructure code. It uses the `lsp` tool's `documentSymbol` operation to enumerate the module's public API, capturing every resource, variable, and output.
To create a README for a Terraform HCL module, Atlas does not rely on memory or outdated specifications. Instead, it uses its `lsp` tool to perform a `documentSymbol` operation, which precisely enumerates all exported elements of your module, such as `variable` blocks, `output` blocks, and `resource` declarations. This ensures that every public interface of your module is accounted for in the documentation. Following this, Atlas employs its `read` tool to delve into the implementation details of each identified export, understanding its behavior. To provide practical context, the `codebase_search` tool is then used to find real-world examples of how these exports are consumed by callers within your repository. This approach guarantees that the generated README is traceable, reflecting the current, actual usage and behavior of your Terraform HCL module, rather than a plausible but potentially incorrect description.
Ensuring accuracy and traceability in Terraform HCL documentation
Atlas ensures the accuracy and traceability of Terraform HCL documentation by generating it directly from source code and verifying every code sample with `bash` in 2026. This process eliminates the common problem of documentation drifting out of sync with the actual module behavior, providing a 100% verifiable README.
The most dangerous part of Terraform HCL is not writing the resource block, but reading the plan it produces. Atlas addresses this by making documentation traceable. After drafting the README with the `write` tool, Atlas takes an extra, crucial step: it verifies every code sample included in the documentation. Using the `bash` tool, Atlas executes these samples, confirming that they are functional and produce the expected results. A code sample that has never been executed is a liability, as it can mislead developers. By running these samples, Atlas guarantees that the examples provided in your `README.md` for your Terraform HCL module are not only syntactically correct but also functionally valid, reflecting the true behavior of the module. This rigorous verification process ensures that the documentation accurately describes what the code actually does today, providing confidence to any developer using your module.
Integrating Atlas with your Terraform HCL development workflow
Atlas direct integrates into your existing Terraform HCL development workflow in 2026, working alongside familiar commands like `terraform init`, `terraform fmt`, and `terraform validate`. You simply run `atlas` in your root module, and it leverages your existing `.tf` files and `.terraform.lock.hcl`.
Integrating Atlas into your Terraform HCL development workflow is straightforward. You begin by running `atlas` in your root module, where your `.tf` files and `.terraform.lock.hcl` reside. Atlas will then read your resources, variables, outputs, and the provider versions pinned in your lock file, gaining a comprehensive understanding of your module's configuration. Beyond documentation, Atlas can assist with refactoring, such as extracting a repeated block into a module or adding a `for_each` instead of counted resources. For safety and correctness, Atlas can run `terraform validate` and `terraform plan` behind a permission prompt. It then reads the plan diff with you before anything is applied, ensuring you understand the implications of any changes. Finally, Atlas can add `terraform test` cases in your `tests/` directory and finish by running `terraform fmt -recursive` to ensure all your Terraform HCL code, including new documentation and tests, adheres to formatting standards.
Safety and review for Terraform HCL code changes with Atlas
Atlas prioritizes safety and review for all Terraform HCL code changes, including documentation updates, through a multi-layered permission system in 2026. Every Atlas tool call is permission-gated, and it drafts a plan in a read-only agent before any modifications are proposed.
When working with sensitive infrastructure code like Terraform HCL, safety is paramount. Atlas implements robust safety mechanisms to ensure that any changes, whether to code or documentation, are thoroughly reviewed and approved. Every Atlas tool call, including `lsp`, `read`, `codebase_search`, `grep`, `write`, and `bash`, is permission-gated against `allow`, `ask`, and `deny` rules. Before making any modifications, Atlas drafts a plan in a read-only plan agent and explicitly asks for your permission before switching to a build agent that can enact changes. For any file edit, such as updating a `README.md` or modifying a `.tf` file, Atlas computes a unified diff and surfaces it for your approval. This allows you to review the exact changes before they are written to disk. Furthermore, Atlas reads `git` branches, status, and diffs, and can stage and create commits on your behalf, ensuring that all changes are tracked and can be rolled back if necessary, providing a secure and auditable workflow for your Terraform HCL projects.
Structuring Terraform HCL READMEs with Atlas
Atlas helps structure your Terraform HCL module READMEs by leveraging existing documentation patterns within your repository in 2026. Instead of inventing a new format, Atlas uses the `grep` tool to find an existing `README.md` and matches its heading structure and tone.
Maintaining consistency in documentation across a large Terraform HCL codebase is crucial for developer experience. Atlas assists in structuring your module READMEs by first using the `grep` tool to search your repository for an existing `README.md` file. This allows Atlas to analyze the established heading structure, tone, and common sections already present in your project's documentation. By matching these existing patterns, Atlas ensures that the new README for your Terraform HCL module direct integrates with your project's documentation standards, rather than introducing a disparate format. This contextual awareness, combined with its ability to extract precise information about your module's `variable` inputs, `output` values, and `resource` definitions, enables Atlas to generate a well-organized, consistent, and highly informative `README.md` that aligns with your team's conventions.
Step by step
- 01Run `terraform init` in your Terraform HCL module's root directory to ensure all providers and modules are downloaded and ready.
- 02Execute `atlas` in your root module, allowing it to read your `.tf` files, `variables.tf`, `outputs.tf`, and the `.terraform.lock.hcl`.
- 03Instruct Atlas to enumerate the module's public API using the `lsp` tool's `documentSymbol` operation, capturing all exports.
- 04Have Atlas read the implementation of each export with the `read` tool and use `codebase_search` to find how callers actually use it in practice.
- 05Ask Atlas to `grep` the repository for an existing `README.md` to match its heading structure and tone for consistency.
- 06Direct Atlas to draft the `README.md` for your Terraform HCL module using the `write` tool, quoting real signatures and file paths.
- 07Verify every code sample in the generated `README.md` by having Atlas run it with the `bash` tool to confirm functionality.
- 08Conclude by having Atlas run `terraform fmt -recursive` to ensure all Terraform HCL files, including the new README, are correctly formatted.
Frequently asked questions
- How does Atlas ensure my Terraform HCL README is up-to-date?
- Atlas ensures your Terraform HCL README is up-to-date by reading your `.tf` files directly, enumerating resources and variables using the `lsp` tool, and verifying code examples with `bash`. This process guarantees the documentation reflects the current state of your Terraform HCL module in 2026, not outdated assumptions.
- Can Atlas help me document a complex Terraform HCL module with many outputs?
- Yes, Atlas uses the `lsp` tool's `documentSymbol` operation to enumerate all exported resources, variables, and outputs in your Terraform HCL module. This comprehensive approach ensures that no public API surface, regardless of complexity, is missed in the generated `README.md`.
- What Terraform HCL commands does Atlas use for verification and safety?
- Atlas can run `terraform validate` and `terraform plan` behind a permission prompt to verify configuration and review changes. Additionally, it verifies code samples in the `README.md` by executing them with the `bash` tool to confirm their functionality within your Terraform HCL environment.
- How does Atlas handle existing README files in my Terraform HCL repository?
- Atlas uses the `grep` tool to search for existing `README.md` files in your repository. This allows it to analyze and match the established heading structure, tone, and common sections, ensuring the new documentation for your Terraform HCL module maintains consistency with your project's standards.
- Is it safe to let Atlas modify my Terraform HCL code or documentation?
- Yes, Atlas is designed with safety in mind for Terraform HCL. Every tool call is permission-gated, and it drafts a plan in a read-only agent. All proposed file edits, including `README.md` updates or `.tf` file changes, are presented as a unified diff for your explicit approval before Atlas writes them, ensuring full control over your codebase.
- Does Atlas support Terraform HCL module registries for package management?
- Atlas integrates with your standard Terraform HCL package management workflow. It expects you to run `terraform init` to download modules from the module registry, and it reads the provider versions pinned in your `.terraform.lock.hcl` file to understand your module's dependencies and context.
Try Atlas in your terminal
The terminal-native AI coding agent. Free core, single binary.
Install AtlasRelated guides
Document a Module with a README Using Atlas (2026 Workflow)
How to document a module with a README using Atlas in 2026: the lsp tool's documentSymbol enumerates the real exports, read supplies the behavior, write emits the README.
Review a pull request in Terraform HCL with Atlas in 2026
Streamline Terraform HCL pull request reviews in 2026 with Atlas. Catch subtle bugs by reviewing diffs with full context, running `terraform test`, and validating plans before application.
Run Atlas Headless in CI for Terraform HCL in 2026
Automate Terraform HCL development in CI pipelines with Atlas. Get machine-readable output, manage permissions, and integrate with terraform init, terraform test, and terraform fmt.
Run the test suite and triage failures in Terraform HCL with Atlas in 2026
In 2026, Terraform HCL developers use Atlas to efficiently run `terraform test` suites, triage failures, and pinpoint distinct root causes from extensive logs, transforming red output into actionable fixes.
Research a Third-Party API Before Integrating it in Terraform HCL with Atlas in 2026
Terraform HCL developers in 2026 use Atlas to research third-party APIs, understand their shape, and safely integrate them. Atlas leverages websearch, webfetch, and guides you through writing, formatting with `terraform
Trace a runtime bug from a stack trace in Terraform HCL with Atlas in 2026
Pinpoint Terraform HCL runtime bugs from production stack traces using Atlas in 2026. Leverage Atlas's AI to navigate .tf files, terraform plan outputs, and terraform test to quickly identify and fix issues without a
Add a Regression Test for a Terraform HCL Bug Fix with Atlas in 2026
Lock in Terraform HCL bug fixes with robust regression tests using Atlas. Learn how to write failing tests, apply fixes, and verify with `terraform test` and `terraform fmt`.
Migrate a Deprecated API Across Every Callsite in Terraform HCL with Atlas in 2026
Efficiently migrate deprecated Terraform HCL APIs across your entire codebase in 2026 using Atlas. Find all callsites, apply context-aware patches, and verify with `terraform test` for a complete, safe transition of