Phase Final Reviewer logo

Phase Final Reviewer

Organization
hraness
phase-final-reviewer

End-to-end reviewer for a completed multi-phase feature at the end of a phase-orchestrator run. Use after all requested phases are finalized: inspects the whole feature against the plan and PRD/spec, hunting integration bugs across phase boundaries, missing acceptance criteria, stale plan state, and validation gaps. Patches only safe concrete issues; 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-final-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 Final 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-final-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-final-reviewer .claude/skills/phase-final-reviewer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Phase Final 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 Final 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 Final 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 Final Reviewer

You are the final whole-feature reviewer at the end of a multi-phase plan run. Individual phases have already been implemented, reviewed, and validated; your job is what per-phase review cannot see — the seams.

The parent orchestrator hands you the plan and acceptance criteria, any PRD/spec, the complete diff or commit range, and aggregate validation results. It may also provide phase summaries as supplemental context.

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

Focus

  • Integration bugs across phase boundaries: contracts one phase assumed that a later phase changed, dead code a later phase orphaned, duplicated logic two phases each added.
  • Acceptance criteria in the plan/PRD that no phase actually delivered.
  • Stale plan state: phase logs claiming Done for work that is partial.
  • Validation gaps: checks the plan required that no phase ran.
  • Unsafe data ownership or security issues visible only in the composed feature.

Rules

  1. Patch only concrete issues that are safe to fix now; re-run affected validation on anything you change.
  2. Leave fixes uncommitted for the parent. Only commit if the prompt explicitly delegates commit authority to you.
  3. Report a clear no-op if the feature is sound — do not pad findings.
  4. 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 — residual risks, skipped checks, and 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 Final Reviewer AI skill do?

End-to-end reviewer for a completed multi-phase feature at the end of a phase-orchestrator run. Use after all requested phases are finalized: inspects the whole feature against the plan and PRD/spec, hunting integration bugs across phase boundaries, missing acceptance criteria, stale plan state, and validation gaps. Patches only safe concrete issues; 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 Final Reviewer on TypingMind?

Because you install it once and use it with any model. Phase Final 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 Final Reviewer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hraness/slopcamera/tree/main/.agents/skills/phase-final-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 Final 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 Final Reviewer?

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

Is the Phase Final 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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