Plannotator v0.21.2

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 v0.21.2 - Software Mirrors

Plannotator v0.21.2 for Windows

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

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

plannotator-win32-arm64.exe | 156.48 MB

plannotator-win32-x64.exe | 159.69 MB

Plannotator v0.21.2 for macOS

plannotator-darwin-arm64 | 108.25 MB

plannotator-darwin-x64 | 112.69 MB

plannotator-paste-darwin-arm64 | 58.24 MB

plannotator-paste-darwin-x64 | 63.07 MB

Plannotator v0.21.2 for Linux

plannotator-linux-arm64 | 143.79 MB

plannotator-linux-x64 | 144.32 MB

plannotator-paste-linux-arm64 | 94.17 MB

plannotator-paste-linux-x64 | 94.7 MB

Plannotator v0.21.2 Release Notes:

Follow @plannotator on X for updates
Missed recent releases?
  • 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
  • v0.19.24: Amp integration, configurable data directory, Auto Mode permission option, Pi plan approval fix
  • v0.19.23: Droid integration, Windows Pi AI fix, quieter update indicator
  • v0.19.22: Safari copy fix in plan viewer, CLAUDE_CONFIG_DIR support for session logs

What's New in v0.21.2

Six PRs land in this release, with most of the work going into code review. You can now run your own Agent Skills as review profiles, and the review engine picker gains two new options — Cursor and OpenCode — alongside the existing Claude and Codex paths. A draft-persistence bug that resurrected deleted annotations is fixed, and Codex users get two improvements from a first-time contributor.

Custom Reviews as Agent Skills

Until now the code review engine ran a fixed review prompt. This release lets you point a review at any Agent Skill you already have installed. Enable a skill as a review profile and the agent runs that skill's instructions against your diff instead of the built-in prompt, so a security skill, a style-guide skill, or any review methodology you've written becomes a one-click review. Findings also gained two new shapes. A review can now attach a finding to an entire file rather than a specific line, and it can raise a general finding that applies to the whole changeset instead of any single location. Whole-file and general findings render in their own sections and flow through to the exported feedback the agent receives, so nothing a reviewer raises gets dropped because it didn't map to a line. PR #955, by @backnotprop.

Cursor and OpenCode Review Engines

The review engine selection now includes Cursor and OpenCode in addition to Claude and Codex. Both run through a unified "marker" protocol: the agent runs its own CLI (agent for Cursor, opencode run for OpenCode) against your changes and returns findings in a delimited block that Plannotator parses back into annotations. The engines are opt-in and only appear when their CLI is installed, and they share the same finding pipeline as the existing engines, so whole-file and general findings work across all four. PR #959, by @backnotprop.

Deleted Review Annotations Stay Deleted

In code review, deleting an annotation and then refreshing the page brought it back. The draft autosave kept the last saved copy, and a deletion wasn't being persisted as a real edit, so the next load restored the annotation the user had removed. This release records deletions with a generation tombstone so they survive a refresh and a late autosave can't revive them, while leaving genuine drafts intact. PR #951 closing #948, reported by @alexanderkreidich.

Codex Ask AI Outside Git Repos

Ask AI on the Codex provider assumed it was running inside a git repository and failed when it wasn't. It now probes for a working tree and skips the git-repo check when there isn't one, so Ask AI works in plain directories that aren't under version control. PR #965, by @ericclemmons.

Codex Desktop Review URL Surfacing

When Plannotator runs inside the Codex desktop app, the session URL wasn't easy to find. It now prints the review URL to the terminal when it detects the Codex desktop host, so the link is visible instead of buried. PR #966, by @ericclemmons.

Additional Changes

  • Landing page section order — the capabilities section now sits above the demos on the marketing site. PR #953, by @backnotprop.

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

  • fix(review): persist annotation deletions so they don't resurrect on refresh by @backnotprop in #951
  • feat(marketing): restructure landing page section order by @backnotprop in #953
  • feat(review): custom reviews as Agent Skills + whole-file/general findings by @backnotprop in #955
  • feat(review): Cursor + OpenCode review engines (unified marker-review) by @backnotprop in #959
  • Allow Codex Ask AI outside git repos by @ericclemmons in #965
  • Improve Codex App review URL discoverability by @ericclemmons in #966

New Contributors

  • @ericclemmons made their first contribution in #965

Contributors

@ericclemmons landed two Codex improvements in his first contributions to the project: making Ask AI work outside git repositories in #965, and surfacing the review URL when running inside the Codex desktop app in #966. Thanks to @alexanderkreidich, who reported in #948 that deleted review annotations reappeared after a refresh — the bug this release fixes. Full Changelog: https://github.com/backnotprop/plannotator/compare/v0.21.1...v0.21.2

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 v0.21.2
Free
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Software Informations:
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Operating System:
Windows / macOS / Linux
Date Added:
2026-06-25T17:35:13.855Z
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