Plannotator v0.27.11

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 v0.27.11 - Software Mirrors
Plannotator v0.27.11 for Windows plannotator-paste-win32-arm64.exe | 90.2 MB plannotator-paste-win32-x64.exe | 93.92 MB plannotator-win32-arm64.exe | 143.53 MB plannotator-win32-x64.exe | 147.25 MB
Plannotator v0.27.11 for macOS plannotator-darwin-arm64 | 114.25 MB plannotator-darwin-x64 | 119.3 MB plannotator-paste-darwin-arm64 | 60.51 MB plannotator-paste-darwin-x64 | 65.97 MB
Plannotator v0.27.11 for Linux plannotator-linux-arm64 | 142.67 MB plannotator-linux-x64 | 143.54 MB plannotator-paste-linux-arm64 | 89.35 MB plannotator-paste-linux-x64 | 90.21 MB
Plannotator v0.27.11 for Other plannotator-0.27.11-release-sbom.cdx.json | 1.61 MB
Plannotator v0.27.11 Release Notes: Follow @plannotator on X for updates Missed recent releases? v0.27.10: Auto-viewed files on scroll, annotation undo/redo, OpenCode 2 slash commands restored, npm 12 agent terminal fix v0.27.9: WebMCP browser-agent tools, HTML refresh from disk, host seams, lazy renderers, Windows uninstall fix v0.27.8: Pi keeps its prompt cache across plan transitions, thumbs-up returns to HTML annotation, embed picker seam v0.27.7: Pi host crash fix on Windows, Call Flow tree cap, jj fork-point base, plannotator knowledge skill + llms.txt v0.27.6: Live app annotation lands on Pi, one interaction model for HTML pages (same-day patch on v0.27.5) v0.27.5: Annotate your running app, Agent TUI placement, collapsed lockfiles, VS Code theme fix, Pi fixes v0.27.4: Portable Guided Review exports, guides.show share links, guide CLI, favicon switcher, jj Call Flow v0.27.3: Folder watcher freeze fix on large repos, first SBOM-attested release pipeline v0.27.2: Mobile plan and code review, Codex CLI 0.147 fix, folder annotate cold-start, configurable markdown extensions v0.27.1: Open-in-editor launch fix, file headers respect Viewed/Git-add visibility toggles v0.27.0: Call Flow analysis, --tailscale remote reviews, review panel remembers your view, Pi rebuild (breaking command rename), focus-mode shortcut v0.26.8: Placed comment markers on HTML pages, shift-click multi-select, live app annotation What's New in v0.27.11 A patch release with one important resource fix, one new safety net, and a CLI fix from a first-time contributor. Every change went through independent adversarial review and a six-agent QA sweep before tagging. OpenCode servers no longer pile up in the background If you had the opencode CLI installed, every Plannotator session quietly started an opencode serve process at launch, just to list OpenCode's models in the Ask AI dropdown. Ending a session with Ctrl-C never cleaned that process up, and every later session found the leftover server and loaded more state into it. Over a day of normal use this grew into a multi-gigabyte orphan process nobody started on purpose. Three things changed. Nothing starts anymore until you actually select OpenCode in Ask AI; most users never do, and now never spawn it. When it does start, each session runs its own private server on its own port instead of sharing one, so sessions can never pile into each other. And the server is now closed when the session ends, including on Ctrl-C. Two visible differences for OpenCode users of Ask AI: the model list fills in when you first select the provider instead of being preloaded, and you will see one opencode serve process per active Plannotator session rather than a shared one. Both are the intended shape of the fix. #1445 Your submitted feedback is now archived locally Every plan decision, code review submission, and annotate submission is now recorded on your machine, under ~/.plannotator/feedback/, organized by project. Each record is one line in an append-only index plus a readable markdown file holding your review text, the excerpts it quoted, and annotation metadata, with lightweight provenance such as file paths and the git ref under review. The reason it exists: feedback used to be gone the moment it was sent. An agent times out, a terminal closes, and the review you wrote is unrecoverable. Now there is a durable record of everything you submitted, and a growing personal archive you can analyze or learn from over time. Herdr Annotate, the terminal-side annotator, writes to the same archive with its own client label, so both tools build one history. The archive stays on your machine and is never transmitted. It is on by default; set PLANNOTATOR_FEEDBACK_HISTORY=0 (or "feedbackHistory": false in ~/.plannotator/config.json) to turn it off, and delete ~/.plannotator/feedback/ to forget what is there. The privacy page documents it. The write path is deliberately fail-safe: if the archive cannot be written for any reason, your feedback still submits exactly as before. #1438 A typo'd command now tells you instead of hanging forever plannotator annotatte README.md used to print nothing and hang until killed, because an unrecognized subcommand fell through to the plan-review hook path, which waits for hook data on stdin that never arrives from a terminal. An unknown subcommand now exits immediately with the misspelled word, a "Did you mean" suggestion, and a pointer to --help. A registry test scrapes the real dispatcher so the known-command list can never drift and reject a valid command. Contributed by @SumeraMartin in #1444, whose diagnosis of the stdin fallthrough was exact, in their first contribution to the project. Additional Changes @plannotator/ui 0.35.2 (with @plannotator/core 0.25.1): hosts embedding the annotation UI can hide the Quick Label tool via the new hideQuickLabel prop on AnnotationToolstrip (forwarded by StickyHeaderLane). Default off; Plannotator's own surfaces are unchanged. #1442. Two broken publishes were caught and corrected the same day: 0.35.0 shipped an unresolvable workspace:* dependency, and 0.35.1 imported a core export the published core 0.25.0 did not contain. The source manifest now pins the exact core version, core 0.25.1 ships the missing exports, and CI installs the packed tarballs outside the monorepo and verifies real imports, TypeScript compilation, and a Vite build, so both failure classes are structurally closed. Use 0.35.2; 0.35.0 and 0.35.1 are deprecated. #1446, #1447 Privacy page: plannotator.ai/privacy now documents the local feedback archive, what a record contains, and how to disable or delete it. Install / Update macOS / Linux: bash curl -fsSL https://plannotator.ai/install.sh | bash Windows: powershell irm https://plannotator.ai/install.ps1 | iex Claude Code Plugin: Run /plugin in Claude Code, find plannotator, and click "Update now". Pi: Update @plannotator/pi-extension to 0.27.11 and restart Pi. OpenCode: Clear cache and restart: bash rm -rf ~/.bun/install/cache/@plannotator What's Changed fix(ai): stop leaking opencode serve processes in #1445 feat(server): durable feedback archive for every submitted review in #1438 fix(cli): exit on an unknown subcommand instead of blocking on stdin by @SumeraMartin in #1444 feat(ui): allow hosts to hide Quick Label in #1442 fix(ui): publish exact core dependency in #1446 fix(packages): publish annotation thread exports in #1447 New Contributors @SumeraMartin made their first contribution in #1444 Community @SumeraMartin found the unknown-subcommand hang, diagnosed the exact stdin fallthrough that caused it, and shipped the fix with a drift-proof test suite in a first contribution that merged as written. The opencode leak was caught during our own multi-agent operations when a monitoring session flagged a multi-gigabyte orphan process, and the feedback archive grew out of repeated user reports of reviews lost to agent timeouts. Thank you. Plannotator gets better because you tell us where it falls short. Full Changelog: v0.27.10...v0.27.11

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.

Free

Download

Software Informations:
Developer:
backnotprop
Operating System:
Windows / macOS / Linux
Date Added:
2026-09-01T23:00:20.217Z
Categories:

Related to Plannotator v0.27.11:

Post a Comment/Report Broken Link: