docs: comprehensive README with action usage, cleanup behavior, custom prompts
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- Quick start example with composite action + matrix strategy - Full action inputs table with descriptions - How sentinel-based cleanup works (explains the reviewer-name concept) - Custom prompt file usage with security review example - CLI usage with all flags - Environment variables table - Token scopes documentation - Setup guide for new repos
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# review-bot
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Automated code review bot for Gitea. Fetches a pull request diff, sends it to an LLM for analysis, and posts a structured review back to the PR.
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AI-powered code review bot for Gitea pull requests. Fetches diff + context, sends to an LLM, and posts a structured review (APPROVE / REQUEST_CHANGES) back to the PR.
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## Features
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- Fetches PR metadata, diff, and CI status from Gitea API
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- Sends context-rich prompts to any OpenAI-compatible LLM
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- Parses structured JSON review responses
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- Posts formatted reviews (APPROVE / REQUEST_CHANGES) back to Gitea
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- Supports custom coding conventions via repo files
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- Zero external dependencies — Go stdlib only
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- **Multi-provider**: OpenAI-compatible and Anthropic Messages API
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- **Context-aware**: Fetches full file content, conventions, language patterns, CI status
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- **Smart budget**: Automatically trims context to fit model token limits
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- **Idempotent reviews**: Deletes previous review before posting new one (one review per bot)
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- **Custom prompts**: Load additional instructions from a file (e.g. security-focused review)
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- **Zero dependencies**: Go stdlib only
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## Usage
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## Quick Start: Composite Action
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The easiest way to use review-bot in your Gitea CI:
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```yaml
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# .gitea/workflows/review.yml
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name: Review
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on:
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pull_request:
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types: [opened, synchronize]
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jobs:
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review:
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runs-on: ubuntu-24.04
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steps:
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- uses: actions/checkout@v4
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- uses: https://gitea.weiker.me/rodin/review-bot/.gitea/actions/review@v0.1.0
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with:
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reviewer-token: ${{ secrets.REVIEW_TOKEN }}
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reviewer-name: code-review
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llm-base-url: ${{ secrets.LLM_BASE_URL }}
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llm-api-key: ${{ secrets.LLM_API_KEY }}
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llm-model: gpt-4.1
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```
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That's it. Every PR gets an automated review.
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## Examples
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### Single reviewer with conventions
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```yaml
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jobs:
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review:
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runs-on: ubuntu-24.04
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steps:
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- uses: actions/checkout@v4
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- uses: https://gitea.weiker.me/rodin/review-bot/.gitea/actions/review@v0.1.0
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with:
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reviewer-token: ${{ secrets.REVIEW_TOKEN }}
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reviewer-name: reviewer
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llm-base-url: ${{ secrets.LLM_BASE_URL }}
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llm-api-key: ${{ secrets.LLM_API_KEY }}
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llm-model: gpt-4.1
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conventions-file: CONVENTIONS.md
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timeout: '600'
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```
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### Two reviewers with different models (diversity of opinion)
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```yaml
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jobs:
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review:
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runs-on: ubuntu-24.04
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strategy:
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matrix:
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include:
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- name: gpt
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model: gpt-4.1
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token_secret: GPT_REVIEW_TOKEN
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- name: claude
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model: claude-sonnet-4-20250514
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token_secret: CLAUDE_REVIEW_TOKEN
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provider: anthropic
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steps:
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- uses: actions/checkout@v4
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- uses: https://gitea.weiker.me/rodin/review-bot/.gitea/actions/review@v0.1.0
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with:
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reviewer-token: ${{ secrets[matrix.token_secret] }}
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reviewer-name: ${{ matrix.name }}
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llm-base-url: ${{ secrets.LLM_BASE_URL }}
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llm-api-key: ${{ secrets.LLM_API_KEY }}
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llm-model: ${{ matrix.model }}
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llm-provider: ${{ matrix.provider }}
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conventions-file: CONVENTIONS.md
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```
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Each reviewer posts independently and only cleans up its own stale reviews.
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### Multiple review types from a single bot account
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Use the same Gitea token but different `reviewer-name` values to run specialized reviews without needing multiple bot accounts:
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```yaml
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jobs:
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review:
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runs-on: ubuntu-24.04
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strategy:
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matrix:
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include:
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- name: code-quality
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model: gpt-4.1
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- name: security
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model: gpt-4.1
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system_prompt_file: .review/SECURITY.md
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- name: performance
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model: gpt-4.1
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system_prompt_file: .review/PERFORMANCE.md
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steps:
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- uses: actions/checkout@v4
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- uses: https://gitea.weiker.me/rodin/review-bot/.gitea/actions/review@v0.1.0
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with:
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reviewer-token: ${{ secrets.REVIEW_TOKEN }}
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reviewer-name: ${{ matrix.name }}
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llm-base-url: ${{ secrets.LLM_BASE_URL }}
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llm-api-key: ${{ secrets.LLM_API_KEY }}
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llm-model: ${{ matrix.model }}
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system-prompt-file: ${{ matrix.system_prompt_file }}
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```
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The sentinel `<!-- review-bot:security -->` ensures the security review only replaces previous security reviews, never the code-quality or performance reviews.
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### With language patterns from another repo
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```yaml
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- uses: https://gitea.weiker.me/rodin/review-bot/.gitea/actions/review@v0.1.0
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with:
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reviewer-token: ${{ secrets.REVIEW_TOKEN }}
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reviewer-name: reviewer
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llm-base-url: ${{ secrets.LLM_BASE_URL }}
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llm-api-key: ${{ secrets.LLM_API_KEY }}
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llm-model: gpt-4.1
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conventions-file: CLAUDE.md
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patterns-repo: rodin/go-patterns,rodin/kubernetes-conventions
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patterns-files: "README.md,patterns/"
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```
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Pattern repos are fetched at review time. The reviewer uses them as criteria for idiomatic code.
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### Dry run (test without posting)
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```yaml
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- uses: https://gitea.weiker.me/rodin/review-bot/.gitea/actions/review@v0.1.0
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with:
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reviewer-token: ${{ secrets.REVIEW_TOKEN }}
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reviewer-name: test
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llm-base-url: ${{ secrets.LLM_BASE_URL }}
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llm-api-key: ${{ secrets.LLM_API_KEY }}
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llm-model: gpt-4.1
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dry-run: 'true'
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```
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Prints the review to CI logs without posting to the PR. Useful for testing prompt changes.
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### Using Anthropic directly
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```yaml
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- uses: https://gitea.weiker.me/rodin/review-bot/.gitea/actions/review@v0.1.0
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with:
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reviewer-token: ${{ secrets.REVIEW_TOKEN }}
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reviewer-name: claude
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llm-base-url: https://api.anthropic.com
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llm-api-key: ${{ secrets.ANTHROPIC_API_KEY }}
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llm-model: claude-sonnet-4-20250514
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llm-provider: anthropic
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```
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## Action Inputs
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| Input | Required | Default | Description |
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|-------|----------|---------|-------------|
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| `reviewer-token` | Yes | — | Gitea token for posting reviews (needs `write:issue`, `write:repository`) |
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| `reviewer-name` | No | `""` | Logical identity for this reviewer. Used as sentinel for idempotent cleanup. Set this when running multiple review bots on the same PR. |
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| `llm-base-url` | Yes | — | LLM API base URL |
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| `llm-api-key` | Yes | — | LLM API key |
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| `llm-model` | Yes | — | Model name |
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| `llm-provider` | No | `openai` | API provider: `openai` or `anthropic` |
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| `conventions-file` | No | `""` | Path to coding conventions file in the repo |
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| `patterns-repo` | No | `""` | Comma-separated repos with language patterns (e.g. `rodin/go-patterns`) |
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| `patterns-files` | No | `README.md` | Files/directories to fetch from pattern repos |
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| `system-prompt-file` | No | `""` | Local file with additional system prompt instructions |
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| `temperature` | No | `0` | LLM temperature (0 = server default) |
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| `timeout` | No | `300` | LLM request timeout in seconds |
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| `dry-run` | No | `false` | Print review to stdout instead of posting |
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| `update-existing` | No | `true` | Delete previous review from same bot before posting. Accepts: true/1/yes or false/0/no |
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| `version` | No | `latest` | review-bot version to install |
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## How Review Cleanup Works
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When `reviewer-name` is set, the bot embeds a hidden sentinel in each review:
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```html
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<!-- review-bot:code-review -->
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```
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On the next run, it finds and deletes any review containing its own sentinel (except the one it just posted). This means:
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- **One review per bot per PR** — no clutter from repeated pushes
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- **Multiple bots coexist** — each only cleans up its own reviews
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- **Same token, different roles** — a single bot account can post "code-review" and "security" reviews without conflict
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- **No extra permissions** — identity comes from the sentinel, not the API
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If `reviewer-name` is empty, cleanup is skipped (reviews stack like before).
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## Custom Review Prompts
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Use `system-prompt-file` to specialize the review focus. The file contents are appended to the base system prompt as "Additional Review Instructions."
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Example `SECURITY_REVIEW.md`:
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```markdown
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You are performing a security-focused code review.
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Focus areas:
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- Injection attacks (SQL, command, path traversal, template)
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- Authentication/Authorization (missing checks, privilege escalation)
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- Secrets exposure (hardcoded credentials, tokens in logs)
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- Input validation (unsanitized input, unsafe deserialization)
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- Race conditions (TOCTOU, unsynchronized shared state)
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Rules:
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- Only report findings with security implications
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- Ignore style, naming, and general code quality
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- MAJOR = exploitable vulnerability, MINOR = hardening opportunity, NIT = theoretical risk
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- If no security-relevant changes exist, APPROVE with empty findings
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```
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## CLI Usage
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```bash
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review-bot \
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@@ -19,71 +236,74 @@ review-bot \
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--repo owner/name \
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--pr 42 \
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--reviewer-token "$GITEA_TOKEN" \
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--reviewer-name "code-review" \
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--llm-base-url https://api.openai.com/v1 \
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--llm-api-key "$OPENAI_API_KEY" \
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--llm-model gpt-4 \
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--reviewer-name "Sonnet" \
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--conventions-file CONVENTIONS.md \
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--dry-run
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--llm-model gpt-4.1 \
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--conventions-file CONVENTIONS.md
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```
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## Environment Variables
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All flags can be set via environment variables:
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All flags have environment variable equivalents:
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| Flag | Env Var | Required | Description |
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|------|---------|----------|-------------|
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| `--gitea-url` | `GITEA_URL` | Yes | Gitea instance base URL |
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| `--repo` | `GITEA_REPO` | Yes | Repository in `owner/name` format |
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| `--pr` | `PR_NUMBER` | Yes | Pull request number |
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| `--reviewer-token` | `REVIEWER_TOKEN` | Yes | Gitea API token for posting reviews |
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| `--llm-base-url` | `LLM_BASE_URL` | Yes | OpenAI-compatible API base URL |
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| `--llm-api-key` | `LLM_API_KEY` | Yes | LLM API key |
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| `--llm-model` | `LLM_MODEL` | Yes | Model identifier |
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| `--reviewer-name` | `REVIEWER_NAME` | No | Display name in review footer |
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| `--conventions-file` | `CONVENTIONS_FILE` | No | Path to conventions file in repo |
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| `--dry-run` | — | No | Print review to stdout instead of posting |
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| Flag | Env Var |
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|------|---------|
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| `--gitea-url` | `GITEA_URL` |
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| `--repo` | `GITEA_REPO` |
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| `--pr` | `PR_NUMBER` |
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| `--reviewer-token` | `REVIEWER_TOKEN` |
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| `--reviewer-name` | `REVIEWER_NAME` |
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| `--llm-base-url` | `LLM_BASE_URL` |
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| `--llm-api-key` | `LLM_API_KEY` |
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| `--llm-model` | `LLM_MODEL` |
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| `--llm-provider` | `LLM_PROVIDER` |
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| `--conventions-file` | `CONVENTIONS_FILE` |
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| `--patterns-repo` | `PATTERNS_REPO` |
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| `--patterns-files` | `PATTERNS_FILES` |
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| `--system-prompt-file` | `SYSTEM_PROMPT_FILE` |
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| `--llm-temperature` | `LLM_TEMPERATURE` |
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| `--llm-timeout` | `LLM_TIMEOUT` |
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| `--update-existing` | `UPDATE_EXISTING` |
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## Adding to a Gitea Repository
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## Setup
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1. Build the binary or use the CI workflow approach (build in CI).
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1. **Create a Gitea bot account** (e.g. `review-bot`)
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2. **Generate a token** with scopes: `write:issue`, `write:repository`
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3. **Add secrets** to your Gitea repo (Settings → Actions → Secrets):
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- `REVIEW_TOKEN` — the bot's Gitea token
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- `LLM_BASE_URL` — your LLM endpoint
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- `LLM_API_KEY` — your LLM key
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4. **Add the workflow** (see Quick Start above)
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2. Add secrets to your Gitea repo (Settings → Actions → Secrets):
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- `SONNET_REVIEW_TOKEN` — Gitea token for the Sonnet reviewer account
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- `GPT_REVIEW_TOKEN` — Gitea token for the GPT reviewer account
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- `LLM_BASE_URL` — Your LLM API endpoint
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- `LLM_API_KEY` — Your LLM API key
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### Token Scopes Required
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3. Copy `.gitea/workflows/ci.yml` to your repo (or adapt it).
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| Scope | Purpose |
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|-------|---------|
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| `write:issue` | Post and delete reviews |
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| `write:repository` | Read PR diffs, file content, commit statuses |
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4. On every PR, the bot will:
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- Run tests and vet
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- Build review-bot
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- Post reviews from each configured LLM reviewer
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No `read:user` scope needed — the bot identifies itself from the review response.
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## Development
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```bash
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# Run tests
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go test ./...
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# Run vet
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go vet ./...
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# Build
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go test ./... # Unit tests
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go vet ./... # Static analysis
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go build -o review-bot ./cmd/review-bot
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# Integration tests (requires env vars)
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# Integration tests (requires env vars set)
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go test -tags=integration ./...
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```
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## Architecture
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```
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cmd/review-bot/ CLI entrypoint
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gitea/ Gitea API client
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llm/ OpenAI-compatible LLM client
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cmd/review-bot/ CLI entrypoint + orchestration
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gitea/ Gitea API client (reviews, PRs, files)
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llm/ Multi-provider LLM client (OpenAI + Anthropic)
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review/ Prompt building, response parsing, formatting
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budget/ Token estimation + context trimming
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```
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## License
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Reference in New Issue
Block a user