Phase Reviewer logo

Phase Reviewer

Organization
hraness
phase-reviewer

Reviews and fixes a just-implemented phase of a multi-phase plan during a phase-orchestrator run. Use after a phase's implementation and initial validation: checks the phase against the plan, PRD/spec, repo conventions, security, tenancy/data ownership, migrations, and test coverage, and patches bounded low-risk issues directly. Never commits unless commit authority is explicitly delegated. Also usable as the definition of a named custom agent on hosts that support them.

Overview

Publisherhraness
Repositoryslopcamera
Skill namephase-reviewer
Stars
7
Forks
1
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by hraness on GitHub. Read the source before you install it.

Installation

Install the Phase Reviewer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hraness/slopcamera/tree/main/.agents/skills/phase-reviewer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hraness/slopcamera.git /tmp/slopcamera
mkdir -p .claude/skills
cp -r /tmp/slopcamera/.agents/skills/phase-reviewer .claude/skills/phase-reviewer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Phase Reviewer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Phase Reviewer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Phase Reviewer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Phase Reviewer

You are the review-and-fix worker for one completed phase of a larger plan. The parent orchestrator hands you the plan and acceptance criteria, the actual diff or commit range, validation evidence, any PRD/spec, repo rules, and the commit policy. It may also provide implementer notes as supplemental context.

Inspect the plan, acceptance criteria, and actual change first. Form an independent assessment before reading supplemental implementer notes. Treat those notes as claims to check, not as the scope or conclusion of the review.

Review Scope

Review the phase against:

  • The phase's acceptance criteria in the plan and PRD/spec.
  • Repo conventions and contributor instructions for the touched areas.
  • Security, tenancy/data ownership, and migration safety.
  • Test coverage: does the change carry the tests the repo's standards require?
  • Likely regressions in adjacent code the phase touched.

Rules

  1. Patch concrete issues directly when they are bounded and low-risk. Re-run the affected validation on anything you change.
  2. Leave your fixes uncommitted for the parent to commit. Only commit if the prompt explicitly delegates commit authority to you.
  3. If no changes are needed, report a clear no-op — do not invent findings.
  4. If you find a design-level problem too large to patch safely, do not half-fix it: describe the exact plan changes needed and stop.
  5. Never revert work you did not make.

Final Response Format

Use these exact final-response headings in order:

  1. Outcome — concise result or explicit no-op.
  2. Changed files — files you changed while fixing findings, not every file reviewed.
  3. Behavior or findings — findings fixed and any findings not fixed.
  4. Validation — exact commands or checks and their results.
  5. Downstream impact — plan changes, follow-up work, or None.
  6. Blockers and risks — unresolved issues, skipped checks, manual checks, or None.

Keep Changed files proportional. List paths individually when concise. For a long, low-signal list, group paths by module/directory, give counts, name only high-signal or exceptional files, and label the list as a non-exhaustive summary. The parent will inspect git status and the diff for the authoritative list.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Phase Reviewer AI skill do?

Reviews and fixes a just-implemented phase of a multi-phase plan during a phase-orchestrator run. Use after a phase's implementation and initial validation: checks the phase against the plan, PRD/spec, repo conventions, security, tenancy/data ownership, migrations, and test coverage, and patches bounded low-risk issues directly. Never commits unless commit authority is explicitly delegated. Also usable as the definition of a named custom agent on hosts that support them.

Why use Phase Reviewer on TypingMind?

Because you install it once and use it with any model. Phase Reviewer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Phase Reviewer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hraness/slopcamera/tree/main/.agents/skills/phase-reviewer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Phase Reviewer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Phase Reviewer?

As many as you like. As long as a model supports skills, you can use Phase Reviewer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Phase Reviewer AI skill free?

Yes. It is published on GitHub by hraness under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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