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 v0.28.4 - Software Mirrors |
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Plannotator v0.28.4 for Windowsplannotator-win32-x64.exe | 149.57 MB plannotator-win32-arm64.exe | 146.54 MB |
Plannotator v0.28.4 for macOSplannotator-paste-darwin-x64 | 65.97 MB plannotator-paste-darwin-arm64 | 60.51 MB |
Plannotator v0.28.4 for Linuxplannotator-paste-linux-x64 | 89.3 MB plannotator-paste-linux-arm64 | 89.35 MB |
Plannotator v0.28.4 Source Code |
Plannotator v0.28.4 Release Notes:Follow @plannotator on X for updatesMissed recent releases?
What's New in v0.28.4Seven PRs, one from a community contributor. Your comments now survive an agent editing the file, the agent can see and close the reviews it opened, and two fixes make sure everything you write reaches the agent.Your comments come back after the agent edits the fileAnnotate drafts used to be saved under the file's content. When an agent edited the file and opened a new review, your unsent comments didn't come back. Drafts are now also saved under the file's path, so reopening the file brings them back even after it changed. Comments whose text moved re-anchor to where the text is now, and comments whose text is gone are kept with an Unanchored tag instead of disappearing. This also works per file in folder reviews, so a file's comments carry between a folder review and a review of that file alone. Exported feedback follows the same rule: a restored comment is labelled with the line its text is on now, and a comment whose text was deleted is sent without a line number rather than a wrong one. Sending your decision still clears the draft. One visible change: a comment that can't find its text anywhere now always shows the Unanchored tag. Before, some of those (share-link imports, comments posted by outside tools) failed silently. (#1710, #1717)The agent can list and close the reviews it openedWith the Claude Code mod, theplannotator tool has two new actions. list shows the reviews opened in this conversation (by the tool or your /plannotator-* commands) with how many of your comments are unsent. close closes one or all of them. Closing works like your own Close but keeps your unsent comments as a draft, sends nothing back to the agent, and the tab says the agent closed it. Plan reviews are listed but can't be closed this way. Every result and decision message now carries a short session id (pn-…) so the agent can tell its reviews apart.
Review servers now refuse a second decision once a review is decided, so late feedback can no longer report success after a close and then be lost. With an older plannotator binary the mod only stops a review's process after confirming it is Plannotator; on CLIs 0.24 to 0.28.3 a decision made in the second before such a stop can still be lost, so update the binary.
(#1709)
Review feedback on the PR description no longer gets droppedCode review used to treat any feedback with no code comments as the "posted to GitHub/GitLab/Bitbucket" status message. Comments on the PR description, PR comment notes and VS Code editor comments travel only in the feedback text, so a review made of only those was silently dropped under the Claude Code mod. The page now marks a real platform post explicitly, and every host (the Claude Code mod, OpenCode and Pi) delivers everything else, with the usual "address these changes" framing. The Claude Code plugin also guards against the old behavior when it runs with aplannotator binary from 0.28.0 to 0.28.3, but updating the binary is the real fix.
(#1719)
Pi's own thinking levels in Ask AIWhen Ask AI uses the Pi provider (no connected session, for example in remote mode), each model now offers exactly the thinking levels Pi reports for it: no Off where the model can't turn reasoning off, Max and XHigh only where the model supports them, and no picker for models without reasoning. Auto sends nothing and leaves Pi's default. Levels are only offered on Pi 0.84.3 or newer, because older Pi versions saved the chosen level as your global default. Model names now read "Name (provider)". (#1704, by @josdirksen)Additional Changes
Install / UpdatemacOS / Linux:plannotator binary update separately, so run the install script above as well. In a terminal:
/plugin marketplace update plannotator, then open /plugin → Installed → plannotator → Update now.
Pi:
What's Changed
Contributors@josdirksen brought Pi's thinking levels into Ask AI, reading them from the installed Pi so each model offers exactly what it supports. Full Changelog: v0.28.3...v0.28.4 |
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:
Receive agent-generated plans
Review proposed actions
Add feedback
Approve or reject changes
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.
Developer:
backnotprop
Operating System:
Windows / macOS / Linux
Date Added:
2026-10-05T23:03:41.669Z
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