Configure .lgtmaybe.yml¶

Place a .lgtmaybe.yml file at the root of your repository to control how lgtmaybe reviews pull requests. CLI flags override file values; the file provides defaults for all runs.

Full example¶

provider: openai
model: gpt-5.5
min_severity: low
include_paths:
  - "src/**"
  - "lib/**"
exclude_paths:
  - "**/__pycache__/**"
  - "**/*.min.js"
max_files: 30
max_input_tokens: 80000
categories:
  - security
  - correctness
  - tests

Field reference¶

See Reference: Config for the full schema with types and defaults.

provider¶

Which LLM backend to use. One of openai, openrouter, anthropic, bedrock, vertex, ollama.

provider: anthropic

model¶

The model identifier for the chosen provider. Format varies by provider:

Provider	Example model IDs
openai	`gpt-5.5`
anthropic	`claude-sonnet-4-6`, `claude-haiku-4-5`
openrouter	`anthropic/claude-sonnet-4-6`
bedrock	`anthropic.claude-sonnet-4-6`, `anthropic.claude-haiku-4-5`
vertex	`gemini-3-pro`, `gemini-3.5-flash`
ollama	`qwen3.6:27b`, `gemma4:e4b`

min_severity¶

The minimum severity level to report. Findings below this threshold are suppressed. Ordered low to high: info, low, medium, high, critical.

min_severity: medium   # suppresses info and low findings

Default: info (all findings reported).

include_paths / exclude_paths¶

Glob patterns to restrict which files in the diff are reviewed. include_paths acts as an allowlist; exclude_paths acts as a denylist applied after the allowlist. Both default to empty (all files included).

include_paths:
  - "src/**"
exclude_paths:
  - "src/generated/**"
  - "**/*.lock"

max_files¶

Maximum number of changed files to include in the review. Files beyond this limit are skipped. Reduces token usage on large PRs.

max_files: 30

Default: 50.

max_input_tokens¶

Hard cap on the number of tokens sent to the model. If the compressed diff exceeds this limit, lgtmaybe truncates it and notes the truncation in the summary.

max_input_tokens: 80000

Default: 100000.

categories¶

Which review lenses to run. The reviewer asks for each category in its own concurrent model call and merges the findings, so a focused prompt concentrates on one concern at a time. One or more of security, correctness, deprecation, tests, documentation, performance, complexity. Narrowing the list trades thoroughness for fewer model calls (and lower token usage).

categories:
  - security
  - correctness

Default: all seven categories.

context_lines¶

Ceiling on the number of unchanged lines added above and below each changed hunk, read from the head revision of the file so the model can review a change in the context of its surrounding code. The actual number used is the smaller of this ceiling and what the token budget allows, so it shrinks automatically on large PRs. Set it to 0 to disable context expansion and review the bare diff (no extra file content is fetched).

context_lines: 10   # at most 10 lines either side of each hunk; 0 disables

Default: 20.

timeout¶

Per-request timeout in seconds for each model call. Left unset, lgtmaybe picks a provider-aware default: 300 s for ollama (local models are slow) and 60 s for cloud providers. Set it explicitly to raise it for a large local model.

timeout: 900   # 15 minutes per call, e.g. for a big model on CPU

Default: auto (ollama 300 s, cloud 60 s). See Run locally with ollama.

structured_output¶

Constrain the model to emit the findings JSON schema using the provider's native JSON mode (litellm response_format). This keeps models — especially local ones — from returning prose or reasoning instead of findings. Leave it on unless a particular model/provider doesn't support structured output, in which case the lenient parser is the fallback.

structured_output: false   # only if your model rejects JSON-schema mode

Default: true.

CLI flag overrides¶

Every config field can be overridden at the command line:

lgtmaybe review \
  --provider anthropic \
  --model claude-haiku-4-5 \
  --min-severity high

Flags take precedence over .lgtmaybe.yml.