Plannotator v0.22.0

Plannotator is an open-source platform designed to review and validate plans and code generated by AI coding agents.

The platform provides a centralized interface where developers can:

  • Review AI-generated plans

  • Annotate proposed actions

  • Approve or reject tasks

  • Inspect code changes

  • Provide structured feedback

  • Improve agent outputs

  • Maintain human oversight

Rather than replacing developers, Plannotator aims to keep humans involved in critical decision-making during AI-assisted development.

As AI coding agents become increasingly capable, developers face a growing challenge: ensuring that AI-generated plans and code changes align with project requirements before they are executed. Plannotator addresses this problem by acting as a review layer between developers and AI coding agents.

Instead of generating code itself, Plannotator focuses on making AI-driven development more transparent and controllable. It allows teams to review, annotate, approve, reject, and refine agent-generated plans and code changes before they affect a project.

Download Plannotator v0.22.0 - Software Mirrors

Plannotator v0.22.0 for Windows

plannotator-paste-win32-arm64.exe | 106.86 MB

plannotator-paste-win32-x64.exe | 110.08 MB

plannotator-win32-arm64.exe | 159.95 MB

plannotator-win32-x64.exe | 163.17 MB

Plannotator v0.22.0 for macOS

plannotator-darwin-arm64 | 111.75 MB

plannotator-darwin-x64 | 116.16 MB

plannotator-paste-darwin-arm64 | 58.24 MB

plannotator-paste-darwin-x64 | 63.07 MB

Plannotator v0.22.0 for Linux

plannotator-linux-arm64 | 147.26 MB

plannotator-linux-x64 | 147.79 MB

plannotator-paste-linux-arm64 | 94.17 MB

plannotator-paste-linux-x64 | 94.7 MB

Plannotator v0.22.0 Release Notes:

Follow @plannotator on X for updates
Missed recent releases?
  • v0.21.4: Markdown math rendering, PR Overview panel with annotatable description and comments, agent instructions in code review, media parsing fixes
  • v0.21.3: File comments in code review, unified click-to-highlight comments, VS Code clipboard/keyboard bridge, Codex Ask AI on app-server transport, CLI subcommand help
  • v0.21.2: Custom reviews as Agent Skills, Cursor + OpenCode review engines, whole-file/general findings, deleted-annotation fix, Codex Ask AI outside git repos
  • v0.21.1: Annotate-last blank-page fix on multi-message sessions
  • v0.21.0: Direct document editing in annotate mode, live git-status file tree, in-app agent terminal, open files in external apps, HTML renders as HTML
  • v0.20.3: Annotations no longer lost when clicking away, off-screen indicator for open comments
  • v0.20.2: Pierre CodeView all-files review, large-PR pipeline and instant-open checkout, unified agent engine selection, Pi programmatic plan mode
  • v0.20.1: Pi extension install hotfix (pinned @pierre/diffs after a broken upstream release)
  • v0.20.0: Multi-repo workspace reviews, semantic diff overview, UI 2.0 themes and plan look chooser, leaner single-source skill install
  • v0.19.27: Kiro CLI integration, Glimpse native window, annotate-last message picker
  • v0.19.26: Amp plugin production fixes, Mermaid rendering fix, Settings flicker fix, update notification toast and shimmer

What's New in v0.22.0

This release rebuilds the code review left panel around how a review actually starts: a git-status view of everything since your base branch is now the default, a Commits panel gives you the branch's history with per-commit diffs, and Guided Review turns any changeset into an agent-organized, chaptered walkthrough with live annotatable diffs. Pi and GitHub Copilot CLI join Cursor and OpenCode as review engines. Five PRs and four direct fixes land, all from the core team, verified by a 24-point QA pass before tagging.

The review now opens on "All changes"

Code reviews used to open on unstaged changes, which answers "what did I just edit" but not the question most reviews start with: "what would a PR show if I pushed right now?" The new default diff answers exactly that. All changes compares the merge base with your base branch against the working tree and includes untracked files — committed work, uncommitted edits, and brand-new files in one view. It renders as a Git status panel with three sections that mirror git status: Committed, Changes, and Untracked. Each row carries viewed tracking, a stage/unstage button, the change-type letter, and +/- counts, so you can stage files as you review without leaving the app. If the base branch has moved on GitHub since your last fetch, a banner offers a one-click fetch so you're reviewing against the real base. A first-run dialog lets you pick your default view and diff type (with live previews), and both remain changeable in Settings → Git or from the review header menu. On repos where a base branch can't be resolved, the review falls back to uncommitted changes rather than hiding committed work. PR #990, by @backnotprop.

Commits panel

The panel toggle gained a third view: Commits, a linear history rail of your branch, newest first, with author avatars and an "In origin/main" divider where your work meets the base. Clicking a commit opens that commit's own diff against its parent — git show, but annotatable — headed by the full commit message rendered as markdown. The toggle is session-scoped: glancing at Commits (or Tree) mid-review never silently changes your saved default, and a review always opens on files, never on a historical commit. Avatars resolve by author email through the repo's forge and fall back to initials when there's no remote or CLI to ask. PR #994, by @backnotprop.

Guided Review

Large changesets are hard to review top-to-bottom in file order. A Guided Review has an agent organize the current changeset — any PR or local diff — into importance-ordered chapters: the heart of the change first, its consequences next, glue last. Each section pairs a prose overview and per-file summaries with the live diffs it covers, and those diffs are the real diff viewer — annotations made inside a guide land in the same review state and export in the same feedback as everywhere else. Open it with the Guide button in the review header or Mod+Shift+G, pick an engine and model, and generate. Sections track their own reviewed state so you can work through a big change across sittings. Guides run on Claude or Codex natively, and on Cursor, OpenCode, Pi, or GitHub Copilot CLI when installed. Every changed file is validated against the real diff server-side, so a guide can never invent files or drop them silently. A one-time intro dialog announces the feature on first open, and the Guide button carries a subtle hint until the first time you use it. PRs #993, #997, and #1000, by @backnotprop.

Pi and GitHub Copilot CLI as review engines

The review and guide launchers gained two engines. Pi rides your existing Pi login (OAuth subscription or keys) with live model discovery and thinking-level control — and the Pi extension can launch Pi, so Pi users get agent reviews with zero extra setup. GitHub Copilot CLI runs in a locked-down non-interactive posture: no write access, a shell allowlist limited to git-family commands, and clean auto-denial for anything else. That brings the engine roster to Claude, Codex, Cursor, OpenCode, Pi, and Copilot — and the engine layer was refactored so the next one is a two-edit change. PRs #993 and #997, by @backnotprop.

Additional Changes

  • Filenames stay visible in the Git status panel — long paths now truncate in the directory portion (ellipsis before the final slash) so the filename always shows; a pathologically long filename truncates at its own end.
  • Commit-diff annotations stay anchored to their commit — annotations made on a historical commit's diff are stamped with that commit, and the exported feedback labels any annotation whose anchor doesn't match the diff being sent, so an agent never reads a commit's line numbers against the working tree.
  • Avatar lookups can't delay the commit list — forge avatar resolution now has a hard 4-second ceiling; on a hanging network the Commits panel loads immediately with initials and picks up avatars once they arrive.
  • Code review reference docs updated — the docs page now describes the since-base default, the three panel views, Guided Review, the full engine roster, and the current server API.

Install / Update

macOS / Linux: 
bash
curl -fsSL https://plannotator.ai/install.sh | bash
Windows: 
powershell
irm https://plannotator.ai/install.ps1 | iex
Extra skills (compound, setup-goal, visual-explainer), opt-in: 
bash
npx skills add backnotprop/plannotator/apps/skills/extra
Claude Code Plugin: Run /plugin in Claude Code, find plannotator, and click "Update now". OpenCode: Clear cache and restart: 
bash
rm -rf ~/.bun/install/cache/@plannotator
Then in opencode.json: 
json
{
  "plugin": ["@plannotator/opencode@latest"]
}
Pi: Install or update the extension: 
bash
pi install npm:@plannotator/pi-extension
Droid: Install via the plugin marketplace: 

droid plugin marketplace add backnotprop/plannotator
droid plugin install plannotator@plannotator
Amp: Install the CLI first, then copy the plugin: 
bash
mkdir -p ~/.config/amp/plugins
curl -fsSL https://raw.githubusercontent.com/backnotprop/plannotator/main/apps/amp-plugin/plannotator.ts \
  -o ~/.config/amp/plugins/plannotator.ts
Kiro CLI: The installer auto-detects Kiro and installs skills automatically. After installing the CLI, launch with: 
bash
kiro-cli chat --agent plannotator
Upgrading from before v0.20.0? Read the v0.20.0 release notes first; that release changed how skills install.

What's Changed

  • feat(review): "All changes" git-status review view by @backnotprop in #990
  • feat(review): Commits panel — linear history rail with per-commit diffs by @backnotprop in #994
  • feat(review): Guided Review + Pi agent-job provider by @backnotprop in #993
  • feat: guide per-file summaries + GitHub Copilot CLI agent engine by @backnotprop in #997
  • feat(review): Guided Reviews intro dialog + Guide button discovery hint by @backnotprop in #1000
  • fix(review): keep the filename visible in git-status rows by @backnotprop
  • fix(review): anchor commit-diff annotations to their commit in feedback by @backnotprop
  • fix(review): avatar lookups can no longer delay /api/commits by @backnotprop
  • docs(marketing): bring the code-review reference up to the since-base era by @backnotprop
Full Changelog: https://github.com/backnotprop/plannotator/compare/v0.21.4...v0.22.0

Key Features of Plannotator

Plan Review System

One of Plannotator's core capabilities is reviewing plans generated by AI agents before execution.

Developers can examine:

  • Proposed tasks

  • Implementation strategies

  • Agent reasoning

  • Planned file modifications

  • Workflow sequences

This visibility helps reduce unintended changes and costly mistakes.

Annotation Tools

The platform allows users to add comments, notes, and guidance directly to AI-generated plans.

These annotations can be used to:

  • Clarify requirements

  • Correct misunderstandings

  • Provide context

  • Guide future agent actions

AI Code Review

Plannotator extends the review process beyond planning by supporting inspection of generated code.

Developers can:

  • Review modifications

  • Analyze diffs

  • Leave comments

  • Request revisions

  • Validate implementation details

This workflow resembles modern pull-request review systems.

Human-in-the-Loop Workflows

A major design goal is ensuring that AI actions remain subject to human approval.

Organizations can establish review processes where important actions require validation before execution.

Open Source Foundation

Plannotator is open source, allowing teams to inspect, modify, and self-host the platform according to their needs.

This transparency is particularly valuable for organizations adopting AI-assisted software development.

User Experience

The interface is designed around review workflows rather than direct code generation.

Instead of interacting with a chatbot, users primarily:

  1. Receive agent-generated plans

  2. Review proposed actions

  3. Add feedback

  4. Approve or reject changes

  5. Monitor execution results

The workflow feels familiar to developers accustomed to pull requests, code reviews, and project planning tools.

Productivity Benefits

As AI coding tools become more autonomous, review processes become increasingly important.

Plannotator helps organizations:

  • Reduce risky AI actions

  • Improve code quality

  • Increase accountability

  • Preserve architectural consistency

  • Encourage collaboration between developers and AI agents

For teams adopting AI-driven development, these safeguards can be as valuable as the coding agents themselves.

Collaboration Features

The platform supports collaborative review workflows where multiple team members can participate in evaluating AI-generated outputs.

This allows:

  • Peer review

  • Team approval processes

  • Shared annotations

  • Collective decision-making

Such features are especially useful for larger engineering teams.

Performance

Because Plannotator focuses on workflow management and review rather than model inference, performance largely depends on the connected AI agents and integrations.

The platform itself is lightweight and primarily serves as an orchestration and review layer.

Open Source Advantages

Being open source provides several benefits:

  • Transparent development

  • Self-hosting capabilities

  • Custom integrations

  • Community contributions

  • Vendor independence

Organizations concerned about compliance, security, or proprietary workflows may find these advantages particularly appealing.

Limitations

Plannotator is designed as a companion tool rather than a complete AI development platform.

Common limitations include:

  • Requires external AI coding agents

  • Best suited for teams already using AI-assisted development

  • Smaller ecosystem than mature developer platforms

  • Additional review steps may slow rapid prototyping

  • Some users may prefer fully autonomous workflows

The software delivers the most value in environments where oversight and quality control are priorities.

Pros

  • Improves transparency of AI-generated plans

  • Supports structured review workflows

  • Human-in-the-loop design

  • Useful annotation system

  • Open source

  • Self-hosting support

  • Familiar review experience for developers

  • Helps reduce AI-generated mistakes

Cons

  • Not a standalone coding agent

  • Requires integration with AI development tools

  • Smaller community than established developer platforms

  • Adds review overhead to workflows

  • Best suited for teams rather than casual users

Who Should Use Plannotator?

Plannotator is ideal for:

  • Software development teams

  • Engineering managers

  • AI-assisted development workflows

  • Organizations adopting coding agents

  • Open-source projects

  • Teams prioritizing code quality and governance

It is particularly valuable for environments where AI-generated code requires oversight before reaching production systems.

Plannotator fills an increasingly important role in the AI development ecosystem by providing visibility and control over AI-generated plans and code changes. Its focus on human oversight, structured reviews, and collaborative workflows makes it a useful companion for modern coding agents. While it is not a replacement for AI coding tools themselves, it offers a practical solution for teams seeking greater confidence and accountability in AI-assisted software development.

Plannotator v0.22.0
Free
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Operating System:
Windows / macOS / Linux
Date Added:
2026-07-05T23:01:30.129Z
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