Plannotator v0.26.4

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 v0.26.4 - Software Mirrors

Plannotator v0.26.4 for Windows

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

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

plannotator-win32-arm64.exe | 159.3 MB

plannotator-win32-x64.exe | 162.51 MB

Plannotator v0.26.4 for macOS

plannotator-darwin-arm64 | 111.09 MB

plannotator-darwin-x64 | 115.5 MB

plannotator-paste-darwin-arm64 | 58.24 MB

plannotator-paste-darwin-x64 | 63.07 MB

Plannotator v0.26.4 for Linux

plannotator-linux-arm64 | 146.61 MB

plannotator-linux-x64 | 147.14 MB

plannotator-paste-linux-arm64 | 94.17 MB

plannotator-paste-linux-x64 | 94.7 MB

Plannotator v0.26.4 Release Notes:

Follow @plannotator on X for updates
Missed recent releases?
  • v0.26.2: Single-file diff tabs render fully, no more silently dropped review files, light/dark theme pairs, palette-matched code blocks
  • v0.26.1: GitButler 0.22.0 compatibility via capability-probed JSON flags
  • v0.26.0: Edit Mode (suggest by editing the diff), Guided Review virtualization, colorblind theme, safe uninstall, installer opt-outs, OpenCode 2 support
  • v0.25.1: Codex no longer launches on review open, annotate-last follows the live conversation, pi-todos mirror, Claude Opus 5, abandoned-gate dismissal
  • v0.25.0: Vim keyboard controls, Approve with Notes, scriptable annotate gates, persistent Guided Reviews, memory and file-watching hardening
  • v0.24.2: Annotate YAML/JSON/TOML config files, XDG data directory support, Codex model catalog update, Cursor sandbox escape hatch
  • v0.24.1: Annotate accepts parent-relative ../ file paths
  • v0.24.0: PR/MR artifact gallery, GitButler review support, port ranges, expanded comment editor, OpenCode + Pi fixes
  • v0.23.1: Startup no longer hangs on large or slow directory trees, Ask AI input stays visible after long responses
  • v0.23.0: Plan approval fix for Claude Code 2.1.199+, annotate mode version diff, binary-only --minimal install, reviews post without attribution
  • v0.22.0: Git-status "All changes" default review view, Commits panel with per-commit diffs, Guided Review, Pi + GitHub Copilot CLI review engines

What's New in v0.26.4

v0.26.4 is a same-day patch on v0.26.3: hovering a human-only skill in the new reference menu caused a constant jitter (the hover warning changed the menu's size, which moved the row out from under the pointer, which hid the warning, in a loop). The menu no longer labels human-only skills at all; since their instructions are injected into the feedback automatically, the distinction did not need surfacing at pick time. Every row now renders identically and hovering can no longer change the menu's geometry (#1236). The full v0.26.3 notes follow. This release adds skill references in comments, gives remote sessions a URL you can actually open from another device, and fixes two small UI annoyances. Nine PRs, including a first contribution from @ivgiuliani.

Reference agent skills in your comments with / or $

While writing a comment in plan review or annotate mode, type / or $ and a menu of your installed agent skills appears: everything discovered under ~/.claude/skills, ~/.codex/skills, and ~/.agents/skills, including skills installed as symlinks. Arrow keys, Tab, Enter, or a click inserts the reference; a comment can carry several. Nothing is preselected, so a stray / or $ in ordinary typing never hijacks Enter, and prose like "a POST /agents endpoint" or "$5/mo" is never mistaken for a reference. Referenced skills change what the agent receives. The exported feedback lists each one with an explicit instruction that you are asking the agent to invoke it. Skills marked disable-model-invocation: true cannot be invoked by the agent, so for those the feedback includes the skill's instructions directly, inside clearly fenced markers, labeled as included at your request. The menu shows a quiet badge on human-only skills so you know which treatment applies before you pick one. The feature landed alongside its own hardening pass, driven by a pre-release QA sweep: a render loop triggered by human-only references was fixed, case-colliding skill names across roots resolve exactly, and the injection markers cannot be forged by a hostile skill body, even with invisible Unicode characters.

Remote sessions advertise a URL you can reach

Until now a remote session (SSH, devcontainer, Tailscale) printed http://localhost:19432, which is useless from the phone or laptop you actually want to review on. Set PLANNOTATOR_URL_HOST to a hostname or IP that resolves on your network (a Tailscale MagicDNS name, a tailnet IP) and every advertised session URL uses it. The override is display-only and deliberately strict: it accepts a bare hostname, IPv4, or bracketed IPv6, and anything carrying a scheme, port, path, or credentials warns once and falls back to localhost. Binding is still governed by PLANNOTATOR_REMOTE, and local sessions ignore the override entirely (with a warning telling you why), so a tailnet-only name can never break same-machine workflows. It can also be set persistently via ~/.plannotator/config.json ({ "urlHost": "host" }).

Full branch names in the worktree switcher

Long branch names in the review header's worktree switcher were truncated with no way to read the rest. Hovering an entry now shows the complete branch name as a tooltip.

Additional Changes

  • "Hide tools" now hides everything. In HTML annotate sessions, hiding the tools also hides the collapsed sidebar tab flags on the left edge, so the page gets the full window (#1226)
  • Archive sharing docs corrected. The docs now describe what archive mode actually does with sharing (#1176, closing #1172)
  • Test reliability. The PowerShell installer tests tolerate pwsh cold starts (#1227) and the diff renderer's test mocks restore correctly regardless of file order (#1230)

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". 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

What's Changed

  • fix(review): show the full branch name when hovering the worktree switcher by @ivgiuliani in #1223
  • feat: add PLANNOTATOR_URL_HOST display-only override for advertised URLs by @backnotprop in #1225
  • fix(annotate): hide the collapsed sidebar tab flags when tools are hidden by @backnotprop in #1226
  • test(install): give the PowerShell scanner tests room for pwsh cold start by @backnotprop in #1227
  • feat(comments): reference agent skills with / or $ in plan review and annotate comments by @backnotprop in #1229
  • fix(test): make the @pierre/diffs mock restore actually restore by @backnotprop in #1230
  • docs: correct archive sharing posture by @backnotprop in #1176
  • fix(editor): stop the skill-content priming effect from re-render looping by @backnotprop in #1234
  • fix(skills): harden skill references before first release by @backnotprop in #1235
  • fix(skills): remove the human-only menu treatment and its hover jitter by @backnotprop in #1236

New Contributors

  • @ivgiuliani made their first contribution in #1223

Community

@ivgiuliani noticed truncated branch names in the worktree switcher and fixed it directly. First contribution, and a clean one. @centdix filed the original request for network-reachable session URLs (#657), and @maxim and @prvnsmpth added the deployment details (Tailscale setups, concrete environment variable shape) that the implementation followed. Full Changelog: https://github.com/backnotprop/plannotator/compare/v0.26.2...v0.26.4

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:

  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 v0.26.4
Free
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Software Informations:
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Operating System:
Windows / macOS / Linux
Date Added:
2026-08-07T23:02:06.757Z
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