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Pre Publish Review

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code-yeongyu
pre-publish-review

Nuclear-grade 12-agent pre-publish release gate. Runs /get-unpublished-changes to detect all changes since last npm release, spawns up to 10 ultrabrain agents for deep per-change analysis, invokes /review-work (orchestrator manual QA plus one gate reviewer) for holistic review, and 1 oracle for overall release synthesis. Runs ONLY when the user explicitly asks for a pre-publish review — a plain publish/release request MUST NOT trigger this; /publish ships directly. Triggers: 'pre-publish review', 'review before publish', 'release review', 'pre-release review', 'ready to publish?', 'can I publish?', 'pre-publish', 'safe to publish', 'publishing review', 'pre-publish check'.

Overview

Publishercode-yeongyu
Repositoryoh-my-openagent
Skill namepre-publish-review
Stars
70K
Forks
5.7K
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by code-yeongyu on GitHub. Read the source before you install it.

Installation

Install the Pre Publish Review 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/code-yeongyu/oh-my-openagent/tree/dev/.agents/skills/pre-publish-review
  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/code-yeongyu/oh-my-openagent.git /tmp/oh-my-openagent
mkdir -p .claude/skills
cp -r /tmp/oh-my-openagent/.agents/skills/pre-publish-review .claude/skills/pre-publish-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pre Publish Review 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 Pre Publish Review 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 Pre Publish Review 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.

Pre-Publish Review — 12-Agent Release Gate

Three-agent-layer review before publishing to npm. Every layer covers a different angle, and every result is mapped onto the release layers below.

LayerAgentsTypeWhat They Check
Per-Change Deep Diveup to 10ultrabrainEach logical change group individually — correctness, edge cases, pattern adherence
Holistic Review1 (+ orchestrator QA)review-workManual QA by the review orchestrator, then one gate reviewer covering goal compliance, code quality, security, and missed context across the full changeset
Release Synthesis1oracleOverall release readiness, version bump, breaking changes, deployment risk

Release Layer Taxonomy

Every phase classifies evidence and risk across:

Release LayerScopeRequired version decision
omo pure componentsCore packages, MCP packages, shared skills, reusable scripts, platform binary inputsPatch/minor/major impact for shared logic consumed by adapters.
omo opencodeRoot oh-my-opencode / oh-my-openagent, src/, OpenCode plugin hooks/tools/CLI/config/docs, .opencode/, .agents/Semver bump for the OpenCode/OpenAgent npm release.
omo codexpackages/omo-codex, lazycodex-ai, Codex plugin metadata/hooks, bundled MCP runtimes, code-yeongyu/lazycodex marketplace payloadCodex adapter bump, LazyCodex npm publish risk, and marketplace/GitHub release need.

Phase 0: Detect Unpublished Changes

Run /get-unpublished-changes FIRST. This is the single source of truth for what changed and must include omo pure components, omo opencode, and omo codex layer-specific version recommendations.

skill(name="get-unpublished-changes")

This command automatically:

  • Detects published npm version vs local version
  • Lists all commits since last release
  • Reads actual diffs (not just commit messages) to describe REAL changes
  • Groups changes by type (feat/fix/refactor/docs) with scope
  • Identifies breaking changes
  • Recommends a layer-specific version bump plus one overall workflow bump

Save the full output — it feeds directly into Phase 1 grouping and all agent prompts.

Then capture raw data needed by agent prompts:

bash
# Extract versions (already in /get-unpublished-changes output)
PUBLISHED=$(npm view oh-my-opencode version 2>/dev/null || echo "not published")
LOCAL=$(node -p "require('./package.json').version" 2>/dev/null || echo "unknown")

# Raw data for agents (diffs, file lists)
COMMITS=$(git log "v${PUBLISHED}"..HEAD --oneline 2>/dev/null || echo "no commits")
COMMIT_COUNT=$(echo "$COMMITS" | wc -l | tr -d ' ')
DIFF_STAT=$(git diff "v${PUBLISHED}"..HEAD --stat 2>/dev/null || echo "no diff")
CHANGED_FILES=$(git diff --name-only "v${PUBLISHED}"..HEAD 2>/dev/null || echo "none")
FILE_COUNT=$(echo "$CHANGED_FILES" | wc -l | tr -d ' ')

If PUBLISHED is "not published", this is a first release — use the full git history instead.

Phase 1: Parse Changes into Groups

Use the /get-unpublished-changes output as the starting point — it already groups by scope and type.

Grouping strategy:

  1. Start from the /get-unpublished-changes analysis which already categorizes by feat/fix/refactor/docs with scope
  2. Further split by module/area — changes touching the same module or feature area belong together
  3. Target up to 10 groups. If fewer than 10 commits, each commit is its own group. If more than 10 logical areas, merge the smallest groups.
  4. For each group, extract:
    • Group name: Short descriptive label (e.g., "agent-model-resolution", "hook-system-refactor")
    • Release layer(s): omo pure components, omo opencode, omo codex
    • Commits: List of commit hashes and messages
    • Files: Changed files in this group
    • Diff: The relevant portion of the full diff (git diff v${PUBLISHED}..HEAD -- {group files})

Phase 2: Spawn All Agents

Launch ALL agents in a single turn. Every agent uses run_in_background=true. No sequential launches.

Layer 1: Ultrabrain Per-Change Analysis (up to 10)

For each change group, spawn one ultrabrain agent. Each gets only its portion of the diff — not the full changeset.

task(
  category="ultrabrain",
  model="gpt-5.6-sol",
  run_in_background=true,
  load_skills=[],
  description="Deep analysis: {GROUP_NAME}",
  prompt="""
<review_type>PER-CHANGE DEEP ANALYSIS</review_type>
<change_group>{GROUP_NAME}</change_group>

<project>oh-my-opencode (npm package)</project>
<published_version>{PUBLISHED}</published_version>
<target_version>{LOCAL}</target_version>

<commits>
{GROUP_COMMITS — hash and message for each commit in this group}
</commits>

<changed_files>
{GROUP_FILES — files changed in this group}
</changed_files>

<diff>
{GROUP_DIFF — only the diff for this group's files}
</diff>

<file_contents>
{Read and include full content of each changed file in this group}
</file_contents>

You are reviewing a specific subset of changes heading into an npm release. Focus exclusively on THIS change group. Other groups are reviewed by parallel agents.

ANALYSIS CHECKLIST:

1. **Intent Clarity**: What is this change trying to do? Is the intent clear from the code and commit messages? If you have to guess, that's a finding.

2. **Correctness**: Trace through the logic for 3+ scenarios. Does the code actually do what it claims? Off-by-one errors, null handling, async edge cases, resource cleanup.

3. **Breaking Changes**: Does this change alter any public API, config format, CLI behavior, or hook contract? If yes, is it backward compatible? Would existing users be surprised?

4. **Pattern Adherence**: Does the new code follow the established patterns visible in the existing file contents? New patterns where old ones exist = finding.

5. **Edge Cases**: What inputs or conditions would break this? Empty arrays, undefined values, concurrent calls, very large inputs, missing config fields.

6. **Error Handling**: Are errors properly caught and propagated? No empty catch blocks? No swallowed promises?

7. **Type Safety**: Any `as any`, `@ts-ignore`, `@ts-expect-error`? Loose typing where strict is possible?

8. **Test Coverage**: Are the behavioral changes covered by tests? Are the tests meaningful or just coverage padding?

9. **Side Effects**: Could this change break something in a different module? Check imports and exports — who depends on what changed?

10. **Release Risk**: On a scale of SAFE / CAUTION / RISKY — how confident are you this change won't cause issues in production?

OUTPUT FORMAT:
<group_name>{GROUP_NAME}</group_name>
<verdict>PASS or FAIL</verdict>
<risk>SAFE / CAUTION / RISKY</risk>
<summary>2-3 sentence assessment of this change group</summary>
<has_breaking_changes>YES or NO</has_breaking_changes>
<breaking_change_details>If YES, describe what breaks and for whom</breaking_change_details>
<findings>
  For each finding:
  - [CRITICAL/MAJOR/MINOR] Category: Description
  - File: path (line range)
  - Evidence: specific code reference
  - Suggestion: how to fix
</findings>
<blocking_issues>Issues that MUST be fixed before publish. Empty if PASS.</blocking_issues>
""")

Layer 2: Holistic Review via /review-work (one gate reviewer)

Spawn a sub-agent that loads the /review-work skill. The review-work skill runs manual QA on the real surface itself, then launches ONE gate reviewer (oracle) that audits goal compliance, code quality, security, missed context, and the QA evidence. The review passes only on a clean QA matrix plus APPROVE.

task(
  category="unspecified-high",
  model="gpt-5.6-sol",
  run_in_background=true,
  load_skills=["review-work"],
  description="Run /review-work on all unpublished changes",
  prompt="""
Run /review-work on the unpublished changes between v{PUBLISHED} and HEAD.

GOAL: Review all changes heading into npm publish of oh-my-opencode. These changes span {COMMIT_COUNT} commits across {FILE_COUNT} files.

CONSTRAINTS:
- This is a plugin published to npm — public API stability matters
- TypeScript strict mode, Bun runtime
- No `as any`, `@ts-ignore`, `@ts-expect-error`
- Factory pattern (createXXX) for tools, hooks, agents
- kebab-case files, barrel exports, no catch-all files

BACKGROUND: Pre-publish review of oh-my-opencode, an OpenCode plugin with 1268 TypeScript files, 160k LOC. Changes since v{PUBLISHED} are about to be published.

The diff base is: git diff v{PUBLISHED}..HEAD

Follow the /review-work skill flow exactly — run the manual QA phase, launch the gate reviewer, and collect its verdict. Do NOT skip the QA phase or the reviewer.
""")

Layer 3: Oracle Release Synthesis (1 agent)

The oracle gets the full picture — all commits, full diff stat, and changed file list. It provides the final release readiness assessment.

task(
  subagent_type="oracle",
  model="gpt-5.6-sol",
  run_in_background=true,
  load_skills=[],
  description="Oracle: overall release synthesis and version bump recommendation",
  prompt="""
<review_type>RELEASE SYNTHESIS — OVERALL ASSESSMENT</review_type>

<project>oh-my-opencode (npm package)</project>
<published_version>{PUBLISHED}</published_version>
<local_version>{LOCAL}</local_version>

<all_commits>
{ALL COMMITS since published version — hash, message, author, date}
</all_commits>

<diff_stat>
{DIFF_STAT — files changed, insertions, deletions}
</diff_stat>

<changed_files>
{CHANGED_FILES — full list of modified file paths}
</changed_files>

<full_diff>
{FULL_DIFF — the complete git diff between published version and HEAD}
</full_diff>

<file_contents>
{Read and include full content of KEY changed files — focus on public API surfaces, config schemas, agent definitions, hook registrations, tool registrations}
</file_contents>

You are the final gate before an npm publish. 10 ultrabrain agents are reviewing individual changes and the review-work gate reviewer is doing the holistic review. Your job is the bird's-eye view that those focused reviews might miss.

SYNTHESIS CHECKLIST:

1. **Release Coherence**: Do these changes tell a coherent story? Or is this a grab-bag of unrelated changes that should be split into multiple releases?

2. **Version Bump**: Based on semver:
   - PATCH: Bug fixes only, no behavior changes
   - MINOR: New features, backward-compatible changes
   - MAJOR: Breaking changes to public API, config format, or behavior
   Recommend the correct bump for each release layer and the overall workflow with specific justification.

3. **Breaking Changes Audit**: Exhaustively list every change that could break existing users. Check:
   - Config schema changes (new required fields, removed fields, renamed fields)
   - Agent behavior changes (different prompts, different model routing)
   - Hook contract changes (new parameters, removed hooks, renamed hooks)
   - Tool interface changes (new required params, different return types)
   - CLI changes (new commands, changed flags, different output)
   - Skill format changes (SKILL.md schema changes)

4. **Migration Requirements**: If there are breaking changes, what migration steps do users need? Is there auto-migration in place?

5. **Dependency Changes**: New dependencies added? Dependencies removed? Version bumps? Any supply chain risk?

6. **Changelog Draft**: Write a draft changelog entry grouped by:
   - feat: New features
   - fix: Bug fixes
   - refactor: Internal changes (no user impact)
   - breaking: Breaking changes with migration instructions
   - docs: Documentation changes

7. **Deployment Risk Assessment**:
   - SAFE: Routine changes, well-tested, low risk
   - CAUTION: Significant changes but manageable risk
   - RISKY: Large surface area changes, insufficient testing, or breaking changes without migration
   - BLOCK: Critical issues found, do NOT publish

8. **Post-Publish Monitoring**: What should be monitored after publish? Error rates, specific features, user feedback channels.

OUTPUT FORMAT:
<verdict>SAFE / CAUTION / RISKY / BLOCK</verdict>
<recommended_version_bump>PATCH / MINOR / MAJOR</recommended_version_bump>
<layer_specific_version_bump>omo pure components: PATCH/MINOR/MAJOR; omo opencode: PATCH/MINOR/MAJOR; omo codex: PATCH/MINOR/MAJOR</layer_specific_version_bump>
<version_bump_justification>Why this bump level</version_bump_justification>
<release_coherence>Assessment of whether changes belong in one release</release_coherence>
<breaking_changes>
  Exhaustive list, or "None" if none.
  For each:
  - What changed
  - Who is affected
  - Migration steps
</breaking_changes>
<changelog_draft>
  Ready-to-use changelog entry
</changelog_draft>
<deployment_risk>
  Overall risk assessment with specific concerns
</deployment_risk>
<monitoring_recommendations>
  What to watch after publish
</monitoring_recommendations>
<blocking_issues>Issues that MUST be fixed before publish. Empty if SAFE.</blocking_issues>
""")

Phase 3: Collect Results

As agents complete (system notifications), collect via background_output(task_id="...").

Track completion in a table:

#AgentTypeStatusVerdict
1-10Ultrabrain: {group_name}ultrabrainpending—
11Review-Work Coordinatorunspecified-highpending—
12Release Synthesis Oracleoraclepending—

Do NOT deliver the final report until ALL agents have completed.


Phase 4: Final Verdict

<verdict_logic>

BLOCK if:

  • Oracle verdict is BLOCK
  • Any ultrabrain found CRITICAL blocking issues
  • Review-work failed on any MAIN agent

RISKY if:

  • Oracle verdict is RISKY
  • Multiple ultrabrains returned CAUTION or FAIL
  • Review-work passed but with significant findings

CAUTION if:

  • Oracle verdict is CAUTION
  • A few ultrabrains flagged minor issues
  • Review-work passed cleanly

SAFE if:

  • Oracle verdict is SAFE
  • All ultrabrains passed
  • Review-work passed

</verdict_logic>

Compile the final report:

markdown
# Pre-Publish Review — oh-my-opencode

## Release: v{PUBLISHED} -> v{LOCAL}
**Commits:** {COMMIT_COUNT} | **Files Changed:** {FILE_COUNT} | **Agents:** {AGENT_COUNT}

---

## Overall Verdict: SAFE / CAUTION / RISKY / BLOCK

## Recommended Version Bump: PATCH / MINOR / MAJOR
{Justification from Oracle}

## Layer-specific Version Recommendation

| Layer | Recommendation | Reason |
|---|---|---|
| omo pure components | PATCH/MINOR/MAJOR | ... |
| omo opencode | PATCH/MINOR/MAJOR | ... |
| omo codex | PATCH/MINOR/MAJOR | ... |

---

## Per-Change Analysis (Ultrabrains)

| # | Change Group | Verdict | Risk | Breaking? | Blocking Issues |
|---|-------------|---------|------|-----------|-----------------|
| 1 | {name} | PASS/FAIL | SAFE/CAUTION/RISKY | YES/NO | {count or "none"} |
| ... | ... | ... | ... | ... | ... |

### Blocking Issues from Per-Change Analysis
{Aggregated from all ultrabrains — deduplicated}

---

## Holistic Review (Review-Work)

| # | Review Area | Verdict | Confidence |
|---|------------|---------|------------|
| 1 | Manual QA (orchestrator, real surface) | PASS/FAIL | - |
| 2 | Gate Review (goal, code quality, security, context, QA audit) | APPROVE/REJECT | HIGH/MED/LOW |

### Blocking Issues from Holistic Review
{Aggregated from review-work}

---

## Release Synthesis (Oracle)

### Breaking Changes
{From Oracle — exhaustive list or "None"}

### Changelog Draft
{From Oracle — ready to use}

### Deployment Risk
{From Oracle — specific concerns}

### Post-Publish Monitoring
{From Oracle — what to watch}

---

## All Blocking Issues (Prioritized)
{Deduplicated, merged from all three layers, ordered by severity}

## Recommendations
{If BLOCK/RISKY: exactly what to fix, in priority order}
{If CAUTION: suggestions worth considering before publish}
{If SAFE: non-blocking improvements for future}

Anti-Patterns

ViolationSeverity
Publishing without waiting for all agentsCRITICAL
Spawning ultrabrains sequentially instead of in parallelCRITICAL
Using run_in_background=false for any agentCRITICAL
Skipping the Oracle synthesisHIGH
Not reading file contents for Oracle (it cannot read files)HIGH
Grouping all changes into 1-2 ultrabrains instead of distributingHIGH
Delivering verdict before all agents completeHIGH
Not including diff in ultrabrain promptsMAJOR

Frequently asked questions

What does the Pre Publish Review AI skill do?

Nuclear-grade 12-agent pre-publish release gate. Runs /get-unpublished-changes to detect all changes since last npm release, spawns up to 10 ultrabrain agents for deep per-change analysis, invokes /review-work (orchestrator manual QA plus one gate reviewer) for holistic review, and 1 oracle for overall release synthesis. Runs ONLY when the user explicitly asks for a pre-publish review — a plain publish/release request MUST NOT trigger this; /publish ships directly. Triggers: 'pre-publish review', 'review before publish', 'release review', 'pre-release review', 'ready to publish?', 'can I pu...

Why use Pre Publish Review on TypingMind?

Because you install it once and use it with any model. Pre Publish Review 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 Pre Publish Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/code-yeongyu/oh-my-openagent/tree/dev/.agents/skills/pre-publish-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pre Publish Review?

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 Pre Publish Review?

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

Is the Pre Publish Review AI skill free?

It is published on GitHub by code-yeongyu. Check the repository for licensing terms. 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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